75 FR 23306 - Southern Nuclear Operating Company, et al.: Supplementary Notice of Hearing and Opportunity To...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-03

...'' field when using either the Web-based search (advanced search) engine or the ADAMS FIND tool in Citrix... should enter ``05200011'' in the ``Docket Number'' field in the web-based search (advanced search) engine... ML100740441. To search for documents in ADAMS using Vogtle Units 3 and 4 COL application docket numbers, 52...

Finding My Needle in the Haystack: Effective Personalized Re-ranking of Search Results in Prospector

NASA Astrophysics Data System (ADS)

König, Florian; van Velsen, Lex; Paramythis, Alexandros

This paper provides an overview of Prospector, a personalized Internet meta-search engine, which utilizes a combination of ontological information, ratings-based models of user interests, and complementary theme-oriented group models to recommend (through re-ranking) search results obtained from an underlying search engine. Re-ranking brings “closer to the top” those items that are of particular interest to a user or have high relevance to a given theme. A user-based, real-world evaluation has shown that the system is effective in promoting results of interest, but lags behind Google in user acceptance, possibly due to the absence of features popularized by said search engine. Overall, users would consider employing a personalized search engine to perform searches with terms that require disambiguation and / or contextualization.

Querying archetype-based EHRs by search ontology-based XPath engineering.

PubMed

Kropf, Stefan; Uciteli, Alexandr; Schierle, Katrin; Krücken, Peter; Denecke, Kerstin; Herre, Heinrich

2018-05-11

Legacy data and new structured data can be stored in a standardized format as XML-based EHRs on XML databases. Querying documents on these databases is crucial for answering research questions. Instead of using free text searches, that lead to false positive results, the precision can be increased by constraining the search to certain parts of documents. A search ontology-based specification of queries on XML documents defines search concepts and relates them to parts in the XML document structure. Such query specification method is practically introduced and evaluated by applying concrete research questions formulated in natural language on a data collection for information retrieval purposes. The search is performed by search ontology-based XPath engineering that reuses ontologies and XML-related W3C standards. The key result is that the specification of research questions can be supported by the usage of search ontology-based XPath engineering. A deeper recognition of entities and a semantic understanding of the content is necessary for a further improvement of precision and recall. Key limitation is that the application of the introduced process requires skills in ontology and software development. In future, the time consuming ontology development could be overcome by implementing a new clinical role: the clinical ontologist. The introduced Search Ontology XML extension connects Search Terms to certain parts in XML documents and enables an ontology-based definition of queries. Search ontology-based XPath engineering can support research question answering by the specification of complex XPath expressions without deep syntax knowledge about XPaths.

GeoSearcher: Location-Based Ranking of Search Engine Results.

ERIC Educational Resources Information Center

Watters, Carolyn; Amoudi, Ghada

2003-01-01

Discussion of Web queries with geospatial dimensions focuses on an algorithm that assigns location coordinates dynamically to Web sites based on the URL. Describes a prototype search system that uses the algorithm to re-rank search engine results for queries with a geospatial dimension, thus providing an alternative ranking order for search engine…

The History of the Internet Search Engine: Navigational Media and the Traffic Commodity

NASA Astrophysics Data System (ADS)

van Couvering, E.

This chapter traces the economic development of the search engine industry over time, beginning with the earliest Web search engines and ending with the domination of the market by Google, Yahoo! and MSN. Specifically, it focuses on the ways in which search engines are similar to and different from traditional media institutions, and how the relations between traditional and Internet media have changed over time. In addition to its historical overview, a core contribution of this chapter is the analysis of the industry using a media value chain based on audiences rather than on content, and the development of traffic as the core unit of exchange. It shows that traditional media companies failed when they attempted to create vertically integrated portals in the late 1990s, based on the idea of controlling Internet content, while search engines succeeded in creating huge "virtually integrated" networks based on control of Internet traffic rather than Internet content.

PepArML: A Meta-Search Peptide Identification Platform

PubMed Central

Edwards, Nathan J.

2014-01-01

The PepArML meta-search peptide identification platform provides a unified search interface to seven search engines; a robust cluster, grid, and cloud computing scheduler for large-scale searches; and an unsupervised, model-free, machine-learning-based result combiner, which selects the best peptide identification for each spectrum, estimates false-discovery rates, and outputs pepXML format identifications. The meta-search platform supports Mascot; Tandem with native, k-score, and s-score scoring; OMSSA; MyriMatch; and InsPecT with MS-GF spectral probability scores — reformatting spectral data and constructing search configurations for each search engine on the fly. The combiner selects the best peptide identification for each spectrum based on search engine results and features that model enzymatic digestion, retention time, precursor isotope clusters, mass accuracy, and proteotypic peptide properties, requiring no prior knowledge of feature utility or weighting. The PepArML meta-search peptide identification platform often identifies 2–3 times more spectra than individual search engines at 10% FDR. PMID:25663956

Development and Evaluation of Thesauri-Based Bibliographic Biomedical Search Engine

ERIC Educational Resources Information Center

Alghoson, Abdullah

2017-01-01

Due to the large volume and exponential growth of biomedical documents (e.g., books, journal articles), it has become increasingly challenging for biomedical search engines to retrieve relevant documents based on users' search queries. Part of the challenge is the matching mechanism of free-text indexing that performs matching based on…

Agreement between Medline searches using the Medline-CD-Rom and Internet Pubmed, BioMedNet, Medscape and Gateway search-engines.

PubMed

Caro-Rojas, Rosa Angela; Eslava-Schmalbach, Javier H

2005-01-01

To compare the information obtained from the Medline database using Internet commercial search engines with that obtained from a compact disc (Medline-CD). An agreement study was carried out based on 101 clinical scenarios provided by specialists in internal medicine, pharmacy, gynaecology-obstetrics, surgery and paediatrics. 175 search strategies were employed using the connector AND plus text within quotation marks. The search was limited to 1991-1999. Internet search-engines were selected by common criteria. Identical search strategies were independently applied to and masked from Internet search engines, as well as the Medline-CD. 3,488 articles were obtained using 129 search strategies. Agreement with the Medline-CD was 54% for PubMed, 57% for Gateway, 54% for Medscape and 65% for BioMedNet. The highest agreement rate for a given speciality (paediatrics) was 78.1% for BioMedNet, having greater -/- than +/+ agreement. Even though free access to Medline has encouraged the boom and growth of evidence-based medicine, these results must be considered within the context of which search engine was selected for doing the searches. The Internet search engines studied showed a poor agreement with the Medline-CD, the rate of agreement differing according to speciality, thus significantly affecting searches and their reproducibility. Software designed for conducting Medline database searches, including the Medline-CD, must be standardised and validated.

An open-source, mobile-friendly search engine for public medical knowledge.

PubMed

Samwald, Matthias; Hanbury, Allan

2014-01-01

The World Wide Web has become an important source of information for medical practitioners. To complement the capabilities of currently available web search engines we developed FindMeEvidence, an open-source, mobile-friendly medical search engine. In a preliminary evaluation, the quality of results from FindMeEvidence proved to be competitive with those from TRIP Database, an established, closed-source search engine for evidence-based medicine.

Informedia at TRECVID 2003: Analyzing and Searching Broadcast News Video

DTIC Science & Technology

2004-11-03

browsing interface to browse the top-ranked shots according to the different classifiers. Color and texture based image search engines were also...different classifiers. Color and texture based image search engines were also optimized better performance. This “new” interface was evaluated as

Improving sensitivity in proteome studies by analysis of false discovery rates for multiple search engines.

PubMed

Jones, Andrew R; Siepen, Jennifer A; Hubbard, Simon J; Paton, Norman W

2009-03-01

LC-MS experiments can generate large quantities of data, for which a variety of database search engines are available to make peptide and protein identifications. Decoy databases are becoming widely used to place statistical confidence in result sets, allowing the false discovery rate (FDR) to be estimated. Different search engines produce different identification sets so employing more than one search engine could result in an increased number of peptides (and proteins) being identified, if an appropriate mechanism for combining data can be defined. We have developed a search engine independent score, based on FDR, which allows peptide identifications from different search engines to be combined, called the FDR Score. The results demonstrate that the observed FDR is significantly different when analysing the set of identifications made by all three search engines, by each pair of search engines or by a single search engine. Our algorithm assigns identifications to groups according to the set of search engines that have made the identification, and re-assigns the score (combined FDR Score). The combined FDR Score can differentiate between correct and incorrect peptide identifications with high accuracy, allowing on average 35% more peptide identifications to be made at a fixed FDR than using a single search engine.

IntegromeDB: an integrated system and biological search engine.

PubMed

Baitaluk, Michael; Kozhenkov, Sergey; Dubinina, Yulia; Ponomarenko, Julia

2012-01-19

With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback.

New Architectures for Presenting Search Results Based on Web Search Engines Users Experience

ERIC Educational Resources Information Center

Martinez, F. J.; Pastor, J. A.; Rodriguez, J. V.; Lopez, Rosana; Rodriguez, J. V., Jr.

2011-01-01

Introduction: The Internet is a dynamic environment which is continuously being updated. Search engines have been, currently are and in all probability will continue to be the most popular systems in this information cosmos. Method: In this work, special attention has been paid to the series of changes made to search engines up to this point,…

PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface.

PubMed

Uszkoreit, Julian; Maerkens, Alexandra; Perez-Riverol, Yasset; Meyer, Helmut E; Marcus, Katrin; Stephan, Christian; Kohlbacher, Oliver; Eisenacher, Martin

2015-07-02

Protein inference connects the peptide spectrum matches (PSMs) obtained from database search engines back to proteins, which are typically at the heart of most proteomics studies. Different search engines yield different PSMs and thus different protein lists. Analysis of results from one or multiple search engines is often hampered by different data exchange formats and lack of convenient and intuitive user interfaces. We present PIA, a flexible software suite for combining PSMs from different search engine runs and turning these into consistent results. PIA can be integrated into proteomics data analysis workflows in several ways. A user-friendly graphical user interface can be run either locally or (e.g., for larger core facilities) from a central server. For automated data processing, stand-alone tools are available. PIA implements several established protein inference algorithms and can combine results from different search engines seamlessly. On several benchmark data sets, we show that PIA can identify a larger number of proteins at the same protein FDR when compared to that using inference based on a single search engine. PIA supports the majority of established search engines and data in the mzIdentML standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.

Global polar geospatial information service retrieval based on search engine and ontology reasoning

USGS Publications Warehouse

Chen, Nengcheng; E, Dongcheng; Di, Liping; Gong, Jianya; Chen, Zeqiang

2007-01-01

In order to improve the access precision of polar geospatial information service on web, a new methodology for retrieving global spatial information services based on geospatial service search and ontology reasoning is proposed, the geospatial service search is implemented to find the coarse service from web, the ontology reasoning is designed to find the refined service from the coarse service. The proposed framework includes standardized distributed geospatial web services, a geospatial service search engine, an extended UDDI registry, and a multi-protocol geospatial information service client. Some key technologies addressed include service discovery based on search engine and service ontology modeling and reasoning in the Antarctic geospatial context. Finally, an Antarctica multi protocol OWS portal prototype based on the proposed methodology is introduced.

Quantitative evaluation of recall and precision of CAT Crawler, a search engine specialized on retrieval of Critically Appraised Topics.

PubMed

Dong, Peng; Wong, Ling Ling; Ng, Sarah; Loh, Marie; Mondry, Adrian

2004-12-10

Critically Appraised Topics (CATs) are a useful tool that helps physicians to make clinical decisions as the healthcare moves towards the practice of Evidence-Based Medicine (EBM). The fast growing World Wide Web has provided a place for physicians to share their appraised topics online, but an increasing amount of time is needed to find a particular topic within such a rich repository. A web-based application, namely the CAT Crawler, was developed by Singapore's Bioinformatics Institute to allow physicians to adequately access available appraised topics on the Internet. A meta-search engine, as the core component of the application, finds relevant topics following keyword input. The primary objective of the work presented here is to evaluate the quantity and quality of search results obtained from the meta-search engine of the CAT Crawler by comparing them with those obtained from two individual CAT search engines. From the CAT libraries at these two sites, all possible keywords were extracted using a keyword extractor. Of those common to both libraries, ten were randomly chosen for evaluation. All ten were submitted to the two search engines individually, and through the meta-search engine of the CAT Crawler. Search results were evaluated for relevance both by medical amateurs and professionals, and the respective recall and precision were calculated. While achieving an identical recall, the meta-search engine showed a precision of 77.26% (+/-14.45) compared to the individual search engines' 52.65% (+/-12.0) (p < 0.001). The results demonstrate the validity of the CAT Crawler meta-search engine approach. The improved precision due to inherent filters underlines the practical usefulness of this tool for clinicians.

Quantitative evaluation of recall and precision of CAT Crawler, a search engine specialized on retrieval of Critically Appraised Topics

PubMed Central

Dong, Peng; Wong, Ling Ling; Ng, Sarah; Loh, Marie; Mondry, Adrian

2004-01-01

Background Critically Appraised Topics (CATs) are a useful tool that helps physicians to make clinical decisions as the healthcare moves towards the practice of Evidence-Based Medicine (EBM). The fast growing World Wide Web has provided a place for physicians to share their appraised topics online, but an increasing amount of time is needed to find a particular topic within such a rich repository. Methods A web-based application, namely the CAT Crawler, was developed by Singapore's Bioinformatics Institute to allow physicians to adequately access available appraised topics on the Internet. A meta-search engine, as the core component of the application, finds relevant topics following keyword input. The primary objective of the work presented here is to evaluate the quantity and quality of search results obtained from the meta-search engine of the CAT Crawler by comparing them with those obtained from two individual CAT search engines. From the CAT libraries at these two sites, all possible keywords were extracted using a keyword extractor. Of those common to both libraries, ten were randomly chosen for evaluation. All ten were submitted to the two search engines individually, and through the meta-search engine of the CAT Crawler. Search results were evaluated for relevance both by medical amateurs and professionals, and the respective recall and precision were calculated. Results While achieving an identical recall, the meta-search engine showed a precision of 77.26% (±14.45) compared to the individual search engines' 52.65% (±12.0) (p < 0.001). Conclusion The results demonstrate the validity of the CAT Crawler meta-search engine approach. The improved precision due to inherent filters underlines the practical usefulness of this tool for clinicians. PMID:15588311

Survey of Quantification and Distance Functions Used for Internet-based Weak-link Sociological Phenomena

DTIC Science & Technology

2016-03-01

well as the Yahoo search engine and a classic SearchKing HIST algorithm. The co-PI immersed herself in the sociology literature for the relevant...Google matrix, PageRank as well as the Yahoo search engine and a classic SearchKing HIST algorithm. The co-PI immersed herself in the sociology...The PI studied all mathematical literature he can find related to the Google search engine, Google matrix, PageRank as well as the Yahoo search

Essie: A Concept-based Search Engine for Structured Biomedical Text

PubMed Central

Ide, Nicholas C.; Loane, Russell F.; Demner-Fushman, Dina

2007-01-01

This article describes the algorithms implemented in the Essie search engine that is currently serving several Web sites at the National Library of Medicine. Essie is a phrase-based search engine with term and concept query expansion and probabilistic relevancy ranking. Essie’s design is motivated by an observation that query terms are often conceptually related to terms in a document, without actually occurring in the document text. Essie’s performance was evaluated using data and standard evaluation methods from the 2003 and 2006 Text REtrieval Conference (TREC) Genomics track. Essie was the best-performing search engine in the 2003 TREC Genomics track and achieved results comparable to those of the highest-ranking systems on the 2006 TREC Genomics track task. Essie shows that a judicious combination of exploiting document structure, phrase searching, and concept based query expansion is a useful approach for information retrieval in the biomedical domain. PMID:17329729

What Can Pictures Tell Us About Web Pages? Improving Document Search Using Images.

PubMed

Rodriguez-Vaamonde, Sergio; Torresani, Lorenzo; Fitzgibbon, Andrew W

2015-06-01

Traditional Web search engines do not use the images in the HTML pages to find relevant documents for a given query. Instead, they typically operate by computing a measure of agreement between the keywords provided by the user and only the text portion of each page. In this paper we study whether the content of the pictures appearing in a Web page can be used to enrich the semantic description of an HTML document and consequently boost the performance of a keyword-based search engine. We present a Web-scalable system that exploits a pure text-based search engine to find an initial set of candidate documents for a given query. Then, the candidate set is reranked using visual information extracted from the images contained in the pages. The resulting system retains the computational efficiency of traditional text-based search engines with only a small additional storage cost needed to encode the visual information. We test our approach on one of the TREC Million Query Track benchmarks where we show that the exploitation of visual content yields improvement in accuracies for two distinct text-based search engines, including the system with the best reported performance on this benchmark. We further validate our approach by collecting document relevance judgements on our search results using Amazon Mechanical Turk. The results of this experiment confirm the improvement in accuracy produced by our image-based reranker over a pure text-based system.

IntegromeDB: an integrated system and biological search engine

PubMed Central

2012-01-01

Background With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Description Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. Conclusions The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback. PMID:22260095

Research on the optimization strategy of web search engine based on data mining

NASA Astrophysics Data System (ADS)

Chen, Ronghua

2018-04-01

With the wide application of search engines, web site information has become an important way for people to obtain information. People have found that they are growing in an increasingly explosive manner. Web site information is verydifficult to find the information they need, and now the search engine can not meet the need, so there is an urgent need for the network to provide website personalized information service, data mining technology for this new challenge is to find a breakthrough. In order to improve people's accuracy of finding information from websites, a website search engine optimization strategy based on data mining is proposed, and verified by website search engine optimization experiment. The results show that the proposed strategy improves the accuracy of the people to find information, and reduces the time for people to find information. It has an important practical value.

Health literacy and usability of clinical trial search engines.

PubMed

Utami, Dina; Bickmore, Timothy W; Barry, Barbara; Paasche-Orlow, Michael K

2014-01-01

Several web-based search engines have been developed to assist individuals to find clinical trials for which they may be interested in volunteering. However, these search engines may be difficult for individuals with low health and computer literacy to navigate. The authors present findings from a usability evaluation of clinical trial search tools with 41 participants across the health and computer literacy spectrum. The study consisted of 3 parts: (a) a usability study of an existing web-based clinical trial search tool; (b) a usability study of a keyword-based clinical trial search tool; and (c) an exploratory study investigating users' information needs when deciding among 2 or more candidate clinical trials. From the first 2 studies, the authors found that users with low health literacy have difficulty forming queries using keywords and have significantly more difficulty using a standard web-based clinical trial search tool compared with users with adequate health literacy. From the third study, the authors identified the search factors most important to individuals searching for clinical trials and how these varied by health literacy level.

Utilization of a radiology-centric search engine.

PubMed

Sharpe, Richard E; Sharpe, Megan; Siegel, Eliot; Siddiqui, Khan

2010-04-01

Internet-based search engines have become a significant component of medical practice. Physicians increasingly rely on information available from search engines as a means to improve patient care, provide better education, and enhance research. Specialized search engines have emerged to more efficiently meet the needs of physicians. Details about the ways in which radiologists utilize search engines have not been documented. The authors categorized every 25th search query in a radiology-centric vertical search engine by radiologic subspecialty, imaging modality, geographic location of access, time of day, use of abbreviations, misspellings, and search language. Musculoskeletal and neurologic imagings were the most frequently searched subspecialties. The least frequently searched were breast imaging, pediatric imaging, and nuclear medicine. Magnetic resonance imaging and computed tomography were the most frequently searched modalities. A majority of searches were initiated in North America, but all continents were represented. Searches occurred 24 h/day in converted local times, with a majority occurring during the normal business day. Misspellings and abbreviations were common. Almost all searches were performed in English. Search engine utilization trends are likely to mirror trends in diagnostic imaging in the region from which searches originate. Internet searching appears to function as a real-time clinical decision-making tool, a research tool, and an educational resource. A more thorough understanding of search utilization patterns can be obtained by analyzing phrases as actually entered as well as the geographic location and time of origination. This knowledge may contribute to the development of more efficient and personalized search engines.

Finding Information on the World Wide Web: The Retrieval Effectiveness of Search Engines.

ERIC Educational Resources Information Center

Pathak, Praveen; Gordon, Michael

1999-01-01

Describes a study that examined the effectiveness of eight search engines for the World Wide Web. Calculated traditional information-retrieval measures of recall and precision at varying numbers of retrieved documents to use as the bases for statistical comparisons of retrieval effectiveness. Also examined the overlap between search engines.…

Web Searching: A Process-Oriented Experimental Study of Three Interactive Search Paradigms.

ERIC Educational Resources Information Center

Dennis, Simon; Bruza, Peter; McArthur, Robert

2002-01-01

Compares search effectiveness when using query-based Internet search via the Google search engine, directory-based search via Yahoo, and phrase-based query reformulation-assisted search via the Hyperindex browser by means of a controlled, user-based experimental study of undergraduates at the University of Queensland. Discusses cognitive load,…

The Gaze of the Perfect Search Engine: Google as an Infrastructure of Dataveillance

NASA Astrophysics Data System (ADS)

Zimmer, M.

Web search engines have emerged as a ubiquitous and vital tool for the successful navigation of the growing online informational sphere. The goal of the world's largest search engine, Google, is to "organize the world's information and make it universally accessible and useful" and to create the "perfect search engine" that provides only intuitive, personalized, and relevant results. While intended to enhance intellectual mobility in the online sphere, this chapter reveals that the quest for the perfect search engine requires the widespread monitoring and aggregation of a users' online personal and intellectual activities, threatening the values the perfect search engines were designed to sustain. It argues that these search-based infrastructures of dataveillance contribute to a rapidly emerging "soft cage" of everyday digital surveillance, where they, like other dataveillance technologies before them, contribute to the curtailing of individual freedom, affect users' sense of self, and present issues of deep discrimination and social justice.

Accessibility, nature and quality of health information on the Internet: a survey on osteoarthritis.

PubMed

Maloney, S; Ilic, D; Green, S

2005-03-01

This study aims to determine the quality and validity of information available on the Internet about osteoarthritis and to investigate the best way of sourcing this information. Keywords relevant to osteoarthritis were searched across 15 search engines representing medical, general and meta-search engines. Search engine efficiency was defined as the percentage of unique and relevant websites from all websites returned by each search engine. The quality of relevant information was appraised using the DISCERN tool and the concordance of the information offered by the website with the available evidence about osteoarthritis determined. A total of 3443 websites were retrieved, of which 344 were identified as unique and providing information relevant to osteoarthritis. The overall quality of website information was poor. There was no significant difference between types of search engine in sourcing relevant information; however, the information retrieved from medical search engines was of a higher quality. Fewer than a third of the websites identified as offering relevant information cited evidence to support their recommendations. Although the overall quality of website information about osteoarthritis was poor, medical search engines may provide consumers with the opportunity to source high-quality health information on the Internet. In the era of evidence-based medicine, one of the main obstacles to the Internet reaching its potential as a medical resource is the failure of websites to incorporate and attribute evidence-based information.

Where to search top-K biomedical ontologies?

PubMed

Oliveira, Daniela; Butt, Anila Sahar; Haller, Armin; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh

2018-03-20

Searching for precise terms and terminological definitions in the biomedical data space is problematic, as researchers find overlapping, closely related and even equivalent concepts in a single or multiple ontologies. Search engines that retrieve ontological resources often suggest an extensive list of search results for a given input term, which leads to the tedious task of selecting the best-fit ontological resource (class or property) for the input term and reduces user confidence in the retrieval engines. A systematic evaluation of these search engines is necessary to understand their strengths and weaknesses in different search requirements. We have implemented seven comparable Information Retrieval ranking algorithms to search through ontologies and compared them against four search engines for ontologies. Free-text queries have been performed, the outcomes have been judged by experts and the ranking algorithms and search engines have been evaluated against the expert-based ground truth (GT). In addition, we propose a probabilistic GT that is developed automatically to provide deeper insights and confidence to the expert-based GT as well as evaluating a broader range of search queries. The main outcome of this work is the identification of key search factors for biomedical ontologies together with search requirements and a set of recommendations that will help biomedical experts and ontology engineers to select the best-suited retrieval mechanism in their search scenarios. We expect that this evaluation will allow researchers and practitioners to apply the current search techniques more reliably and that it will help them to select the right solution for their daily work. The source code (of seven ranking algorithms), ground truths and experimental results are available at https://github.com/danielapoliveira/bioont-search-benchmark.

Practical and Efficient Searching in Proteomics: A Cross Engine Comparison

PubMed Central

Paulo, Joao A.

2014-01-01

Background Analysis of large datasets produced by mass spectrometry-based proteomics relies on database search algorithms to sequence peptides and identify proteins. Several such scoring methods are available, each based on different statistical foundations and thereby not producing identical results. Here, the aim is to compare peptide and protein identifications using multiple search engines and examine the additional proteins gained by increasing the number of technical replicate analyses. Methods A HeLa whole cell lysate was analyzed on an Orbitrap mass spectrometer for 10 technical replicates. The data were combined and searched using Mascot, SEQUEST, and Andromeda. Comparisons were made of peptide and protein identifications among the search engines. In addition, searches using each engine were performed with incrementing number of technical replicates. Results The number and identity of peptides and proteins differed across search engines. For all three search engines, the differences in proteins identifications were greater than the differences in peptide identifications indicating that the major source of the disparity may be at the protein inference grouping level. The data also revealed that analysis of 2 technical replicates can increase protein identifications by up to 10-15%, while a third replicate results in an additional 4-5%. Conclusions The data emphasize two practical methods of increasing the robustness of mass spectrometry data analysis. The data show that 1) using multiple search engines can expand the number of identified proteins (union) and validate protein identifications (intersection), and 2) analysis of 2 or 3 technical replicates can substantially expand protein identifications. Moreover, information can be extracted from a dataset by performing database searching with different engines and performing technical repeats, which requires no additional sample preparation and effectively utilizes research time and effort. PMID:25346847

The accuracy of Internet search engines to predict diagnoses from symptoms can be assessed with a validated scoring system.

PubMed

Shenker, Bennett S

2014-02-01

To validate a scoring system that evaluates the ability of Internet search engines to correctly predict diagnoses when symptoms are used as search terms. We developed a five point scoring system to evaluate the diagnostic accuracy of Internet search engines. We identified twenty diagnoses common to a primary care setting to validate the scoring system. One investigator entered the symptoms for each diagnosis into three Internet search engines (Google, Bing, and Ask) and saved the first five webpages from each search. Other investigators reviewed the webpages and assigned a diagnostic accuracy score. They rescored a random sample of webpages two weeks later. To validate the five point scoring system, we calculated convergent validity and test-retest reliability using Kendall's W and Spearman's rho, respectively. We used the Kruskal-Wallis test to look for differences in accuracy scores for the three Internet search engines. A total of 600 webpages were reviewed. Kendall's W for the raters was 0.71 (p<0.0001). Spearman's rho for test-retest reliability was 0.72 (p<0.0001). There was no difference in scores based on Internet search engine. We found a significant difference in scores based on the webpage's order on the Internet search engine webpage (p=0.007). Pairwise comparisons revealed higher scores in the first webpages vs. the fourth (corr p=0.009) and fifth (corr p=0.017). However, this significance was lost when creating composite scores. The five point scoring system to assess diagnostic accuracy of Internet search engines is a valid and reliable instrument. The scoring system may be used in future Internet research. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Practical and Efficient Searching in Proteomics: A Cross Engine Comparison.

PubMed

Paulo, Joao A

2013-10-01

Analysis of large datasets produced by mass spectrometry-based proteomics relies on database search algorithms to sequence peptides and identify proteins. Several such scoring methods are available, each based on different statistical foundations and thereby not producing identical results. Here, the aim is to compare peptide and protein identifications using multiple search engines and examine the additional proteins gained by increasing the number of technical replicate analyses. A HeLa whole cell lysate was analyzed on an Orbitrap mass spectrometer for 10 technical replicates. The data were combined and searched using Mascot, SEQUEST, and Andromeda. Comparisons were made of peptide and protein identifications among the search engines. In addition, searches using each engine were performed with incrementing number of technical replicates. The number and identity of peptides and proteins differed across search engines. For all three search engines, the differences in proteins identifications were greater than the differences in peptide identifications indicating that the major source of the disparity may be at the protein inference grouping level. The data also revealed that analysis of 2 technical replicates can increase protein identifications by up to 10-15%, while a third replicate results in an additional 4-5%. The data emphasize two practical methods of increasing the robustness of mass spectrometry data analysis. The data show that 1) using multiple search engines can expand the number of identified proteins (union) and validate protein identifications (intersection), and 2) analysis of 2 or 3 technical replicates can substantially expand protein identifications. Moreover, information can be extracted from a dataset by performing database searching with different engines and performing technical repeats, which requires no additional sample preparation and effectively utilizes research time and effort.

Evaluating Open-Source Full-Text Search Engines for Matching ICD-10 Codes.

PubMed

Jurcău, Daniel-Alexandru; Stoicu-Tivadar, Vasile

2016-01-01

This research presents the results of evaluating multiple free, open-source engines on matching ICD-10 diagnostic codes via full-text searches. The study investigates what it takes to get an accurate match when searching for a specific diagnostic code. For each code the evaluation starts by extracting the words that make up its text and continues with building full-text search queries from the combinations of these words. The queries are then run against all the ICD-10 codes until a match indicates the code in question as a match with the highest relative score. This method identifies the minimum number of words that must be provided in order for the search engines choose the desired entry. The engines analyzed include a popular Java-based full-text search engine, a lightweight engine written in JavaScript which can even execute on the user's browser, and two popular open-source relational database management systems.

Use of controlled vocabularies to improve biomedical information retrieval tasks.

PubMed

Pasche, Emilie; Gobeill, Julien; Vishnyakova, Dina; Ruch, Patrick; Lovis, Christian

2013-01-01

The high heterogeneity of biomedical vocabulary is a major obstacle for information retrieval in large biomedical collections. Therefore, using biomedical controlled vocabularies is crucial for managing these contents. We investigate the impact of query expansion based on controlled vocabularies to improve the effectiveness of two search engines. Our strategy relies on the enrichment of users' queries with additional terms, directly derived from such vocabularies applied to infectious diseases and chemical patents. We observed that query expansion based on pathogen names resulted in improvements of the top-precision of our first search engine, while the normalization of diseases degraded the top-precision. The expansion of chemical entities, which was performed on the second search engine, positively affected the mean average precision. We have shown that query expansion of some types of biomedical entities has a great potential to improve search effectiveness; therefore a fine-tuning of query expansion strategies could help improving the performances of search engines.

An approach in building a chemical compound search engine in oracle database.

PubMed

Wang, H; Volarath, P; Harrison, R

2005-01-01

A searching or identifying of chemical compounds is an important process in drug design and in chemistry research. An efficient search engine involves a close coupling of the search algorithm and database implementation. The database must process chemical structures, which demands the approaches to represent, store, and retrieve structures in a database system. In this paper, a general database framework for working as a chemical compound search engine in Oracle database is described. The framework is devoted to eliminate data type constrains for potential search algorithms, which is a crucial step toward building a domain specific query language on top of SQL. A search engine implementation based on the database framework is also demonstrated. The convenience of the implementation emphasizes the efficiency and simplicity of the framework.

Anatomy and evolution of database search engines-a central component of mass spectrometry based proteomic workflows.

PubMed

Verheggen, Kenneth; Raeder, Helge; Berven, Frode S; Martens, Lennart; Barsnes, Harald; Vaudel, Marc

2017-09-13

Sequence database search engines are bioinformatics algorithms that identify peptides from tandem mass spectra using a reference protein sequence database. Two decades of development, notably driven by advances in mass spectrometry, have provided scientists with more than 30 published search engines, each with its own properties. In this review, we present the common paradigm behind the different implementations, and its limitations for modern mass spectrometry datasets. We also detail how the search engines attempt to alleviate these limitations, and provide an overview of the different software frameworks available to the researcher. Finally, we highlight alternative approaches for the identification of proteomic mass spectrometry datasets, either as a replacement for, or as a complement to, sequence database search engines. © 2017 Wiley Periodicals, Inc.

Balancing Efficiency and Effectiveness for Fusion-Based Search Engines in the "Big Data" Environment

ERIC Educational Resources Information Center

Li, Jieyu; Huang, Chunlan; Wang, Xiuhong; Wu, Shengli

2016-01-01

Introduction: In the big data age, we have to deal with a tremendous amount of information, which can be collected from various types of sources. For information search systems such as Web search engines or online digital libraries, the collection of documents becomes larger and larger. For some queries, an information search system needs to…

Developing a distributed HTML5-based search engine for geospatial resource discovery

NASA Astrophysics Data System (ADS)

ZHOU, N.; XIA, J.; Nebert, D.; Yang, C.; Gui, Z.; Liu, K.

2013-12-01

With explosive growth of data, Geospatial Cyberinfrastructure(GCI) components are developed to manage geospatial resources, such as data discovery and data publishing. However, the efficiency of geospatial resources discovery is still challenging in that: (1) existing GCIs are usually developed for users of specific domains. Users may have to visit a number of GCIs to find appropriate resources; (2) The complexity of decentralized network environment usually results in slow response and pool user experience; (3) Users who use different browsers and devices may have very different user experiences because of the diversity of front-end platforms (e.g. Silverlight, Flash or HTML). To address these issues, we developed a distributed and HTML5-based search engine. Specifically, (1)the search engine adopts a brokering approach to retrieve geospatial metadata from various and distributed GCIs; (2) the asynchronous record retrieval mode enhances the search performance and user interactivity; (3) the search engine based on HTML5 is able to provide unified access capabilities for users with different devices (e.g. tablet and smartphone).

Using Internet Search Engines to Obtain Medical Information: A Comparative Study

PubMed Central

Wang, Liupu; Wang, Juexin; Wang, Michael; Li, Yong; Liang, Yanchun

2012-01-01

Background The Internet has become one of the most important means to obtain health and medical information. It is often the first step in checking for basic information about a disease and its treatment. The search results are often useful to general users. Various search engines such as Google, Yahoo!, Bing, and Ask.com can play an important role in obtaining medical information for both medical professionals and lay people. However, the usability and effectiveness of various search engines for medical information have not been comprehensively compared and evaluated. Objective To compare major Internet search engines in their usability of obtaining medical and health information. Methods We applied usability testing as a software engineering technique and a standard industry practice to compare the four major search engines (Google, Yahoo!, Bing, and Ask.com) in obtaining health and medical information. For this purpose, we searched the keyword breast cancer in Google, Yahoo!, Bing, and Ask.com and saved the results of the top 200 links from each search engine. We combined nonredundant links from the four search engines and gave them to volunteer users in an alphabetical order. The volunteer users evaluated the websites and scored each website from 0 to 10 (lowest to highest) based on the usefulness of the content relevant to breast cancer. A medical expert identified six well-known websites related to breast cancer in advance as standards. We also used five keywords associated with breast cancer defined in the latest release of Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) and analyzed their occurrence in the websites. Results Each search engine provided rich information related to breast cancer in the search results. All six standard websites were among the top 30 in search results of all four search engines. Google had the best search validity (in terms of whether a website could be opened), followed by Bing, Ask.com, and Yahoo!. The search results highly overlapped between the search engines, and the overlap between any two search engines was about half or more. On the other hand, each search engine emphasized various types of content differently. In terms of user satisfaction analysis, volunteer users scored Bing the highest for its usefulness, followed by Yahoo!, Google, and Ask.com. Conclusions Google, Yahoo!, Bing, and Ask.com are by and large effective search engines for helping lay users get health and medical information. Nevertheless, the current ranking methods have some pitfalls and there is room for improvement to help users get more accurate and useful information. We suggest that search engine users explore multiple search engines to search different types of health information and medical knowledge for their own needs and get a professional consultation if necessary. PMID:22672889

Using Internet search engines to obtain medical information: a comparative study.

PubMed

Wang, Liupu; Wang, Juexin; Wang, Michael; Li, Yong; Liang, Yanchun; Xu, Dong

2012-05-16

The Internet has become one of the most important means to obtain health and medical information. It is often the first step in checking for basic information about a disease and its treatment. The search results are often useful to general users. Various search engines such as Google, Yahoo!, Bing, and Ask.com can play an important role in obtaining medical information for both medical professionals and lay people. However, the usability and effectiveness of various search engines for medical information have not been comprehensively compared and evaluated. To compare major Internet search engines in their usability of obtaining medical and health information. We applied usability testing as a software engineering technique and a standard industry practice to compare the four major search engines (Google, Yahoo!, Bing, and Ask.com) in obtaining health and medical information. For this purpose, we searched the keyword breast cancer in Google, Yahoo!, Bing, and Ask.com and saved the results of the top 200 links from each search engine. We combined nonredundant links from the four search engines and gave them to volunteer users in an alphabetical order. The volunteer users evaluated the websites and scored each website from 0 to 10 (lowest to highest) based on the usefulness of the content relevant to breast cancer. A medical expert identified six well-known websites related to breast cancer in advance as standards. We also used five keywords associated with breast cancer defined in the latest release of Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) and analyzed their occurrence in the websites. Each search engine provided rich information related to breast cancer in the search results. All six standard websites were among the top 30 in search results of all four search engines. Google had the best search validity (in terms of whether a website could be opened), followed by Bing, Ask.com, and Yahoo!. The search results highly overlapped between the search engines, and the overlap between any two search engines was about half or more. On the other hand, each search engine emphasized various types of content differently. In terms of user satisfaction analysis, volunteer users scored Bing the highest for its usefulness, followed by Yahoo!, Google, and Ask.com. Google, Yahoo!, Bing, and Ask.com are by and large effective search engines for helping lay users get health and medical information. Nevertheless, the current ranking methods have some pitfalls and there is room for improvement to help users get more accurate and useful information. We suggest that search engine users explore multiple search engines to search different types of health information and medical knowledge for their own needs and get a professional consultation if necessary.

Supporting inter-topic entity search for biomedical Linked Data based on heterogeneous relationships.

PubMed

Zong, Nansu; Lee, Sungin; Ahn, Jinhyun; Kim, Hong-Gee

2017-08-01

The keyword-based entity search restricts search space based on the preference of search. When given keywords and preferences are not related to the same biomedical topic, existing biomedical Linked Data search engines fail to deliver satisfactory results. This research aims to tackle this issue by supporting an inter-topic search-improving search with inputs, keywords and preferences, under different topics. This study developed an effective algorithm in which the relations between biomedical entities were used in tandem with a keyword-based entity search, Siren. The algorithm, PERank, which is an adaptation of Personalized PageRank (PPR), uses a pair of input: (1) search preferences, and (2) entities from a keyword-based entity search with a keyword query, to formalize the search results on-the-fly based on the index of the precomputed Individual Personalized PageRank Vectors (IPPVs). Our experiments were performed over ten linked life datasets for two query sets, one with keyword-preference topic correspondence (intra-topic search), and the other without (inter-topic search). The experiments showed that the proposed method achieved better search results, for example a 14% increase in precision for the inter-topic search than the baseline keyword-based search engine. The proposed method improved the keyword-based biomedical entity search by supporting the inter-topic search without affecting the intra-topic search based on the relations between different entities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evidence-based Medicine Search: a customizable federated search engine.

PubMed

Bracke, Paul J; Howse, David K; Keim, Samuel M

2008-04-01

This paper reports on the development of a tool by the Arizona Health Sciences Library (AHSL) for searching clinical evidence that can be customized for different user groups. The AHSL provides services to the University of Arizona's (UA's) health sciences programs and to the University Medical Center. Librarians at AHSL collaborated with UA College of Medicine faculty to create an innovative search engine, Evidence-based Medicine (EBM) Search, that provides users with a simple search interface to EBM resources and presents results organized according to an evidence pyramid. EBM Search was developed with a web-based configuration component that allows the tool to be customized for different specialties. Informal and anecdotal feedback from physicians indicates that EBM Search is a useful tool with potential in teaching evidence-based decision making. While formal evaluation is still being planned, a tool such as EBM Search, which can be configured for specific user populations, may help lower barriers to information resources in an academic health sciences center.

Evidence-based Medicine Search: a customizable federated search engine

PubMed Central

Bracke, Paul J.; Howse, David K.; Keim, Samuel M.

2008-01-01

Purpose: This paper reports on the development of a tool by the Arizona Health Sciences Library (AHSL) for searching clinical evidence that can be customized for different user groups. Brief Description: The AHSL provides services to the University of Arizona's (UA's) health sciences programs and to the University Medical Center. Librarians at AHSL collaborated with UA College of Medicine faculty to create an innovative search engine, Evidence-based Medicine (EBM) Search, that provides users with a simple search interface to EBM resources and presents results organized according to an evidence pyramid. EBM Search was developed with a web-based configuration component that allows the tool to be customized for different specialties. Outcomes/Conclusion: Informal and anecdotal feedback from physicians indicates that EBM Search is a useful tool with potential in teaching evidence-based decision making. While formal evaluation is still being planned, a tool such as EBM Search, which can be configured for specific user populations, may help lower barriers to information resources in an academic health sciences center. PMID:18379665

Comet: an open-source MS/MS sequence database search tool.

PubMed

Eng, Jimmy K; Jahan, Tahmina A; Hoopmann, Michael R

2013-01-01

Proteomics research routinely involves identifying peptides and proteins via MS/MS sequence database search. Thus the database search engine is an integral tool in many proteomics research groups. Here, we introduce the Comet search engine to the existing landscape of commercial and open-source database search tools. Comet is open source, freely available, and based on one of the original sequence database search tools that has been widely used for many years. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

How Safe Are Kid-Safe Search Engines?

ERIC Educational Resources Information Center

Masterson-Krum, Hope

2001-01-01

Examines search tools available to elementary and secondary school students, both human-compiled and crawler-based, to help direct them to age-appropriate Web sites; analyzes the procedures of search engines labeled family-friendly or kid safe that use filters; and tests the effectiveness of these services to students in school libraries. (LRW)

Andromeda: a peptide search engine integrated into the MaxQuant environment.

PubMed

Cox, Jürgen; Neuhauser, Nadin; Michalski, Annette; Scheltema, Richard A; Olsen, Jesper V; Mann, Matthias

2011-04-01

A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spectra Andromeda is also accessible via a web server. We demonstrate the flexibility of the system by implementing the capability to identify cofragmented peptides, significantly improving the total number of identified peptides.

GeNemo: a search engine for web-based functional genomic data.

PubMed

Zhang, Yongqing; Cao, Xiaoyi; Zhong, Sheng

2016-07-08

A set of new data types emerged from functional genomic assays, including ChIP-seq, DNase-seq, FAIRE-seq and others. The results are typically stored as genome-wide intensities (WIG/bigWig files) or functional genomic regions (peak/BED files). These data types present new challenges to big data science. Here, we present GeNemo, a web-based search engine for functional genomic data. GeNemo searches user-input data against online functional genomic datasets, including the entire collection of ENCODE and mouse ENCODE datasets. Unlike text-based search engines, GeNemo's searches are based on pattern matching of functional genomic regions. This distinguishes GeNemo from text or DNA sequence searches. The user can input any complete or partial functional genomic dataset, for example, a binding intensity file (bigWig) or a peak file. GeNemo reports any genomic regions, ranging from hundred bases to hundred thousand bases, from any of the online ENCODE datasets that share similar functional (binding, modification, accessibility) patterns. This is enabled by a Markov Chain Monte Carlo-based maximization process, executed on up to 24 parallel computing threads. By clicking on a search result, the user can visually compare her/his data with the found datasets and navigate the identified genomic regions. GeNemo is available at www.genemo.org. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

BioCarian: search engine for exploratory searches in heterogeneous biological databases.

PubMed

Zaki, Nazar; Tennakoon, Chandana

2017-10-02

There are a large number of biological databases publicly available for scientists in the web. Also, there are many private databases generated in the course of research projects. These databases are in a wide variety of formats. Web standards have evolved in the recent times and semantic web technologies are now available to interconnect diverse and heterogeneous sources of data. Therefore, integration and querying of biological databases can be facilitated by techniques used in semantic web. Heterogeneous databases can be converted into Resource Description Format (RDF) and queried using SPARQL language. Searching for exact queries in these databases is trivial. However, exploratory searches need customized solutions, especially when multiple databases are involved. This process is cumbersome and time consuming for those without a sufficient background in computer science. In this context, a search engine facilitating exploratory searches of databases would be of great help to the scientific community. We present BioCarian, an efficient and user-friendly search engine for performing exploratory searches on biological databases. The search engine is an interface for SPARQL queries over RDF databases. We note that many of the databases can be converted to tabular form. We first convert the tabular databases to RDF. The search engine provides a graphical interface based on facets to explore the converted databases. The facet interface is more advanced than conventional facets. It allows complex queries to be constructed, and have additional features like ranking of facet values based on several criteria, visually indicating the relevance of a facet value and presenting the most important facet values when a large number of choices are available. For the advanced users, SPARQL queries can be run directly on the databases. Using this feature, users will be able to incorporate federated searches of SPARQL endpoints. We used the search engine to do an exploratory search on previously published viral integration data and were able to deduce the main conclusions of the original publication. BioCarian is accessible via http://www.biocarian.com . We have developed a search engine to explore RDF databases that can be used by both novice and advanced users.

Protein-Level Integration Strategy of Multiengine MS Spectra Search Results for Higher Confidence and Sequence Coverage.

PubMed

Zhao, Panpan; Zhong, Jiayong; Liu, Wanting; Zhao, Jing; Zhang, Gong

2017-12-01

Multiple search engines based on various models have been developed to search MS/MS spectra against a reference database, providing different results for the same data set. How to integrate these results efficiently with minimal compromise on false discoveries is an open question due to the lack of an independent, reliable, and highly sensitive standard. We took the advantage of the translating mRNA sequencing (RNC-seq) result as a standard to evaluate the integration strategies of the protein identifications from various search engines. We used seven mainstream search engines (Andromeda, Mascot, OMSSA, X!Tandem, pFind, InsPecT, and ProVerB) to search the same label-free MS data sets of human cell lines Hep3B, MHCCLM3, and MHCC97H from the Chinese C-HPP Consortium for Chromosomes 1, 8, and 20. As expected, the union of seven engines resulted in a boosted false identification, whereas the intersection of seven engines remarkably decreased the identification power. We found that identifications of at least two out of seven engines resulted in maximizing the protein identification power while minimizing the ratio of suspicious/translation-supported identifications (STR), as monitored by our STR index, based on RNC-Seq. Furthermore, this strategy also significantly improves the peptides coverage of the protein amino acid sequence. In summary, we demonstrated a simple strategy to significantly improve the performance for shotgun mass spectrometry by protein-level integrating multiple search engines, maximizing the utilization of the current MS spectra without additional experimental work.

BIOMedical Search Engine Framework: Lightweight and customized implementation of domain-specific biomedical search engines.

PubMed

Jácome, Alberto G; Fdez-Riverola, Florentino; Lourenço, Anália

2016-07-01

Text mining and semantic analysis approaches can be applied to the construction of biomedical domain-specific search engines and provide an attractive alternative to create personalized and enhanced search experiences. Therefore, this work introduces the new open-source BIOMedical Search Engine Framework for the fast and lightweight development of domain-specific search engines. The rationale behind this framework is to incorporate core features typically available in search engine frameworks with flexible and extensible technologies to retrieve biomedical documents, annotate meaningful domain concepts, and develop highly customized Web search interfaces. The BIOMedical Search Engine Framework integrates taggers for major biomedical concepts, such as diseases, drugs, genes, proteins, compounds and organisms, and enables the use of domain-specific controlled vocabulary. Technologies from the Typesafe Reactive Platform, the AngularJS JavaScript framework and the Bootstrap HTML/CSS framework support the customization of the domain-oriented search application. Moreover, the RESTful API of the BIOMedical Search Engine Framework allows the integration of the search engine into existing systems or a complete web interface personalization. The construction of the Smart Drug Search is described as proof-of-concept of the BIOMedical Search Engine Framework. This public search engine catalogs scientific literature about antimicrobial resistance, microbial virulence and topics alike. The keyword-based queries of the users are transformed into concepts and search results are presented and ranked accordingly. The semantic graph view portraits all the concepts found in the results, and the researcher may look into the relevance of different concepts, the strength of direct relations, and non-trivial, indirect relations. The number of occurrences of the concept shows its importance to the query, and the frequency of concept co-occurrence is indicative of biological relations meaningful to that particular scope of research. Conversely, indirect concept associations, i.e. concepts related by other intermediary concepts, can be useful to integrate information from different studies and look into non-trivial relations. The BIOMedical Search Engine Framework supports the development of domain-specific search engines. The key strengths of the framework are modularity and extensibilityin terms of software design, the use of open-source consolidated Web technologies, and the ability to integrate any number of biomedical text mining tools and information resources. Currently, the Smart Drug Search keeps over 1,186,000 documents, containing more than 11,854,000 annotations for 77,200 different concepts. The Smart Drug Search is publicly accessible at http://sing.ei.uvigo.es/sds/. The BIOMedical Search Engine Framework is freely available for non-commercial use at https://github.com/agjacome/biomsef. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Inefficiency and Bias of Search Engines in Retrieving References Containing Scientific Names of Fossil Amphibians

ERIC Educational Resources Information Center

Brown, Lauren E.; Dubois, Alain; Shepard, Donald B.

2008-01-01

Retrieval efficiencies of paper-based references in journals and other serials containing 10 scientific names of fossil amphibians were determined for seven major search engines. Retrievals were compared to the number of references obtained covering the period 1895-2006 by a Comprehensive Search. The latter was primarily a traditional…

An ontology-based search engine for protein-protein interactions

PubMed Central

2010-01-01

Background Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. Results We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Conclusion Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology. PMID:20122195

An ontology-based search engine for protein-protein interactions.

PubMed

Park, Byungkyu; Han, Kyungsook

2010-01-18

Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology.

'Sciencenet'--towards a global search and share engine for all scientific knowledge.

PubMed

Lütjohann, Dominic S; Shah, Asmi H; Christen, Michael P; Richter, Florian; Knese, Karsten; Liebel, Urban

2011-06-15

Modern biological experiments create vast amounts of data which are geographically distributed. These datasets consist of petabytes of raw data and billions of documents. Yet to the best of our knowledge, a search engine technology that searches and cross-links all different data types in life sciences does not exist. We have developed a prototype distributed scientific search engine technology, 'Sciencenet', which facilitates rapid searching over this large data space. By 'bringing the search engine to the data', we do not require server farms. This platform also allows users to contribute to the search index and publish their large-scale data to support e-Science. Furthermore, a community-driven method guarantees that only scientific content is crawled and presented. Our peer-to-peer approach is sufficiently scalable for the science web without performance or capacity tradeoff. The free to use search portal web page and the downloadable client are accessible at: http://sciencenet.kit.edu. The web portal for index administration is implemented in ASP.NET, the 'AskMe' experiment publisher is written in Python 2.7, and the backend 'YaCy' search engine is based on Java 1.6.

Directing the public to evidence-based online content

PubMed Central

Cooper, Crystale Purvis; Gelb, Cynthia A; Vaughn, Alexandra N; Smuland, Jenny; Hughes, Alexandra G; Hawkins, Nikki A

2015-01-01

To direct online users searching for gynecologic cancer information to accurate content, the Centers for Disease Control and Prevention’s (CDC) ‘Inside Knowledge: Get the Facts About Gynecologic Cancer’ campaign sponsored search engine advertisements in English and Spanish. From June 2012 to August 2013, advertisements appeared when US Google users entered search terms related to gynecologic cancer. Users who clicked on the advertisements were directed to relevant content on the CDC website. Compared with the 3 months before the initiative (March–May 2012), visits to the CDC web pages linked to the advertisements were 26 times higher after the initiative began (June–August 2012) (p<0.01), and 65 times higher when the search engine advertisements were supplemented with promotion on television and additional websites (September 2012–August 2013) (p<0.01). Search engine advertisements can direct users to evidence-based content at a highly teachable moment—when they are seeking relevant information. PMID:25053580

Dark Web 101

DTIC Science & Technology

2016-07-21

Todays internet has multiple webs. The surface web is what Google and other search engines index and pull based on links. Essentially, the surface...financial records, research and development), and personal data (medical records or legal documents). These are all deep web. Standard search engines dont

A natural language based search engine for ICD10 diagnosis encoding.

PubMed

Baud, Robert

2004-01-01

We have developed a multiple step process for implementing an ICD10 search engine. The complexity of the task has been shown and we recommend collecting adequate expertise before starting any implementation. Underestimation of the expert time and inadequate data resources are probable reasons for failure. We also claim that when all conditions are met in term of resource and availability of the expertise, the benefits of a responsive ICD10 search engine will be present and the investment will be successful.

Designing a Syntax-Based Retrieval System for Supporting Language Learning

ERIC Educational Resources Information Center

Tsao, Nai-Lung; Kuo, Chin-Hwa; Wible, David; Hung, Tsung-Fu

2009-01-01

In this paper, we propose a syntax-based text retrieval system for on-line language learning and use a fast regular expression search engine as its main component. Regular expression searches provide more scalable querying and search results than keyword-based searches. However, without a well-designed index scheme, the execution time of regular…

Are cannabis prevalence estimates comparable across countries and regions? A cross-cultural validation using search engine query data.

PubMed

Steppan, Martin; Kraus, Ludwig; Piontek, Daniela; Siciliano, Valeria

2013-01-01

Prevalence estimation of cannabis use is usually based on self-report data. Although there is evidence on the reliability of this data source, its cross-cultural validity is still a major concern. External objective criteria are needed for this purpose. In this study, cannabis-related search engine query data are used as an external criterion. Data on cannabis use were taken from the 2007 European School Survey Project on Alcohol and Other Drugs (ESPAD). Provincial data came from three Italian nation-wide studies using the same methodology (2006-2008; ESPAD-Italia). Information on cannabis-related search engine query data was based on Google search volume indices (GSI). (1) Reliability analysis was conducted for GSI. (2) Latent measurement models of "true" cannabis prevalence were tested using perceived availability, web-based cannabis searches and self-reported prevalence as indicators. (3) Structure models were set up to test the influences of response tendencies and geographical position (latitude, longitude). In order to test the stability of the models, analyses were conducted on country level (Europe, US) and on provincial level in Italy. Cannabis-related GSI were found to be highly reliable and constant over time. The overall measurement model was highly significant in both data sets. On country level, no significant effects of response bias indicators and geographical position on perceived availability, web-based cannabis searches and self-reported prevalence were found. On provincial level, latitude had a significant positive effect on availability indicating that perceived availability of cannabis in northern Italy was higher than expected from the other indicators. Although GSI showed weaker associations with cannabis use than perceived availability, the findings underline the external validity and usefulness of search engine query data as external criteria. The findings suggest an acceptable relative comparability of national (provincial) prevalence estimates of cannabis use that are based on a common survey methodology. Search engine query data are a too weak indicator to base prevalence estimations on this source only, but in combination with other sources (waste water analysis, sales of cigarette paper) they may provide satisfactory estimates. Copyright © 2012. Published by Elsevier B.V.

Cloud parallel processing of tandem mass spectrometry based proteomics data.

PubMed

Mohammed, Yassene; Mostovenko, Ekaterina; Henneman, Alex A; Marissen, Rob J; Deelder, André M; Palmblad, Magnus

2012-10-05

Data analysis in mass spectrometry based proteomics struggles to keep pace with the advances in instrumentation and the increasing rate of data acquisition. Analyzing this data involves multiple steps requiring diverse software, using different algorithms and data formats. Speed and performance of the mass spectral search engines are continuously improving, although not necessarily as needed to face the challenges of acquired big data. Improving and parallelizing the search algorithms is one possibility; data decomposition presents another, simpler strategy for introducing parallelism. We describe a general method for parallelizing identification of tandem mass spectra using data decomposition that keeps the search engine intact and wraps the parallelization around it. We introduce two algorithms for decomposing mzXML files and recomposing resulting pepXML files. This makes the approach applicable to different search engines, including those relying on sequence databases and those searching spectral libraries. We use cloud computing to deliver the computational power and scientific workflow engines to interface and automate the different processing steps. We show how to leverage these technologies to achieve faster data analysis in proteomics and present three scientific workflows for parallel database as well as spectral library search using our data decomposition programs, X!Tandem and SpectraST.

The pond is wider than you think! Problems encountered when searching family practice literature.

PubMed Central

Rosser, W. W.; Starkey, C.; Shaughnessy, R.

2000-01-01

OBJECTIVE: To explain differences in the results of literature searches in British general practice and North American family practice or family medicine. DESIGN: Comparative literature search. SETTING: The Department of Family and Community Medicine at the University of Toronto in Ontario. METHOD: Literature searches on MEDLINE demonstrated that certain search strategies ignored certain key words, depending on the search engine and the search terms chosen. Literature searches using the key words "general practice," "family practice," and "family medicine" combined with the topics "depression" and then "otitis media" were conducted in MEDLINE using four different Web-based search engines: Ovid, HealthGate, PubMed, and Internet Grateful Med. MAIN OUTCOME MEASURES: The number of MEDLINE references retrieved for both topics when searched with each of the three key words, "general practice," "family practice," and "family medicine" using each of the four search engines. RESULTS: For each topic, each search yielded very different articles. Some search engines did a better job of matching the term "general practice" to the terms "family medicine" and "family practice," and thus improved retrieval. The problem of language use extends to the variable use of terminology and differences in spelling between British and American English. CONCLUSION: We need to heighten awareness of literature search problems and the potential for duplication of research effort when some of the literature is ignored, and to suggest ways to overcome the deficiencies of the various search engines. Images Figure 1 Figure 2 PMID:10660792

Towards Identifying and Reducing the Bias of Disease Information Extracted from Search Engine Data

PubMed Central

Huang, Da-Cang; Wang, Jin-Feng; Huang, Ji-Xia; Sui, Daniel Z.; Zhang, Hong-Yan; Hu, Mao-Gui; Xu, Cheng-Dong

2016-01-01

The estimation of disease prevalence in online search engine data (e.g., Google Flu Trends (GFT)) has received a considerable amount of scholarly and public attention in recent years. While the utility of search engine data for disease surveillance has been demonstrated, the scientific community still seeks ways to identify and reduce biases that are embedded in search engine data. The primary goal of this study is to explore new ways of improving the accuracy of disease prevalence estimations by combining traditional disease data with search engine data. A novel method, Biased Sentinel Hospital-based Area Disease Estimation (B-SHADE), is introduced to reduce search engine data bias from a geographical perspective. To monitor search trends on Hand, Foot and Mouth Disease (HFMD) in Guangdong Province, China, we tested our approach by selecting 11 keywords from the Baidu index platform, a Chinese big data analyst similar to GFT. The correlation between the number of real cases and the composite index was 0.8. After decomposing the composite index at the city level, we found that only 10 cities presented a correlation of close to 0.8 or higher. These cities were found to be more stable with respect to search volume, and they were selected as sample cities in order to estimate the search volume of the entire province. After the estimation, the correlation improved from 0.8 to 0.864. After fitting the revised search volume with historical cases, the mean absolute error was 11.19% lower than it was when the original search volume and historical cases were combined. To our knowledge, this is the first study to reduce search engine data bias levels through the use of rigorous spatial sampling strategies. PMID:27271698

Towards Identifying and Reducing the Bias of Disease Information Extracted from Search Engine Data.

PubMed

Huang, Da-Cang; Wang, Jin-Feng; Huang, Ji-Xia; Sui, Daniel Z; Zhang, Hong-Yan; Hu, Mao-Gui; Xu, Cheng-Dong

2016-06-01

The estimation of disease prevalence in online search engine data (e.g., Google Flu Trends (GFT)) has received a considerable amount of scholarly and public attention in recent years. While the utility of search engine data for disease surveillance has been demonstrated, the scientific community still seeks ways to identify and reduce biases that are embedded in search engine data. The primary goal of this study is to explore new ways of improving the accuracy of disease prevalence estimations by combining traditional disease data with search engine data. A novel method, Biased Sentinel Hospital-based Area Disease Estimation (B-SHADE), is introduced to reduce search engine data bias from a geographical perspective. To monitor search trends on Hand, Foot and Mouth Disease (HFMD) in Guangdong Province, China, we tested our approach by selecting 11 keywords from the Baidu index platform, a Chinese big data analyst similar to GFT. The correlation between the number of real cases and the composite index was 0.8. After decomposing the composite index at the city level, we found that only 10 cities presented a correlation of close to 0.8 or higher. These cities were found to be more stable with respect to search volume, and they were selected as sample cities in order to estimate the search volume of the entire province. After the estimation, the correlation improved from 0.8 to 0.864. After fitting the revised search volume with historical cases, the mean absolute error was 11.19% lower than it was when the original search volume and historical cases were combined. To our knowledge, this is the first study to reduce search engine data bias levels through the use of rigorous spatial sampling strategies.

FPS-RAM: Fast Prefix Search RAM-Based Hardware for Forwarding Engine

NASA Astrophysics Data System (ADS)

Zaitsu, Kazuya; Yamamoto, Koji; Kuroda, Yasuto; Inoue, Kazunari; Ata, Shingo; Oka, Ikuo

Ternary content addressable memory (TCAM) is becoming very popular for designing high-throughput forwarding engines on routers. However, TCAM has potential problems in terms of hardware and power costs, which limits its ability to deploy large amounts of capacity in IP routers. In this paper, we propose new hardware architecture for fast forwarding engines, called fast prefix search RAM-based hardware (FPS-RAM). We designed FPS-RAM hardware with the intent of maintaining the same search performance and physical user interface as TCAM because our objective is to replace the TCAM in the market. Our RAM-based hardware architecture is completely different from that of TCAM and has dramatically reduced the costs and power consumption to 62% and 52%, respectively. We implemented FPS-RAM on an FPGA to examine its lookup operation.

Visibiome: an efficient microbiome search engine based on a scalable, distributed architecture.

PubMed

Azman, Syafiq Kamarul; Anwar, Muhammad Zohaib; Henschel, Andreas

2017-07-24

Given the current influx of 16S rRNA profiles of microbiota samples, it is conceivable that large amounts of them eventually are available for search, comparison and contextualization with respect to novel samples. This process facilitates the identification of similar compositional features in microbiota elsewhere and therefore can help to understand driving factors for microbial community assembly. We present Visibiome, a microbiome search engine that can perform exhaustive, phylogeny based similarity search and contextualization of user-provided samples against a comprehensive dataset of 16S rRNA profiles environments, while tackling several computational challenges. In order to scale to high demands, we developed a distributed system that combines web framework technology, task queueing and scheduling, cloud computing and a dedicated database server. To further ensure speed and efficiency, we have deployed Nearest Neighbor search algorithms, capable of sublinear searches in high-dimensional metric spaces in combination with an optimized Earth Mover Distance based implementation of weighted UniFrac. The search also incorporates pairwise (adaptive) rarefaction and optionally, 16S rRNA copy number correction. The result of a query microbiome sample is the contextualization against a comprehensive database of microbiome samples from a diverse range of environments, visualized through a rich set of interactive figures and diagrams, including barchart-based compositional comparisons and ranking of the closest matches in the database. Visibiome is a convenient, scalable and efficient framework to search microbiomes against a comprehensive database of environmental samples. The search engine leverages a popular but computationally expensive, phylogeny based distance metric, while providing numerous advantages over the current state of the art tool.

Improving Concept-Based Web Image Retrieval by Mixing Semantically Similar Greek Queries

ERIC Educational Resources Information Center

Lazarinis, Fotis

2008-01-01

Purpose: Image searching is a common activity for web users. Search engines offer image retrieval services based on textual queries. Previous studies have shown that web searching is more demanding when the search is not in English and does not use a Latin-based language. The aim of this paper is to explore the behaviour of the major search…

Quality Dimensions of Internet Search Engines.

ERIC Educational Resources Information Center

Xie, M.; Wang, H.; Goh, T. N.

1998-01-01

Reviews commonly used search engines (AltaVista, Excite, infoseek, Lycos, HotBot, WebCrawler), focusing on existing comparative studies; considers quality dimensions from the customer's point of view based on a SERVQUAL framework; and groups these quality expectations in five dimensions: tangibles, reliability, responsiveness, assurance, and…

Design implications for task-specific search utilities for retrieval and re-engineering of code

NASA Astrophysics Data System (ADS)

Iqbal, Rahat; Grzywaczewski, Adam; Halloran, John; Doctor, Faiyaz; Iqbal, Kashif

2017-05-01

The importance of information retrieval systems is unquestionable in the modern society and both individuals as well as enterprises recognise the benefits of being able to find information effectively. Current code-focused information retrieval systems such as Google Code Search, Codeplex or Koders produce results based on specific keywords. However, these systems do not take into account developers' context such as development language, technology framework, goal of the project, project complexity and developer's domain expertise. They also impose additional cognitive burden on users in switching between different interfaces and clicking through to find the relevant code. Hence, they are not used by software developers. In this paper, we discuss how software engineers interact with information and general-purpose information retrieval systems (e.g. Google, Yahoo!) and investigate to what extent domain-specific search and recommendation utilities can be developed in order to support their work-related activities. In order to investigate this, we conducted a user study and found that software engineers followed many identifiable and repeatable work tasks and behaviours. These behaviours can be used to develop implicit relevance feedback-based systems based on the observed retention actions. Moreover, we discuss the implications for the development of task-specific search and collaborative recommendation utilities embedded with the Google standard search engine and Microsoft IntelliSense for retrieval and re-engineering of code. Based on implicit relevance feedback, we have implemented a prototype of the proposed collaborative recommendation system, which was evaluated in a controlled environment simulating the real-world situation of professional software engineers. The evaluation has achieved promising initial results on the precision and recall performance of the system.

Improving PHENIX search with Solr, Nutch and Drupal.

NASA Astrophysics Data System (ADS)

Morrison, Dave; Sourikova, Irina

2012-12-01

During its 20 years of R&D, construction and operation the PHENIX experiment at the Relativistic Heavy Ion Collider (RHIC) has accumulated large amounts of proprietary collaboration data that is hosted on many servers around the world and is not open for commercial search engines for indexing and searching. The legacy search infrastructure did not scale well with the fast growing PHENIX document base and produced results inadequate in both precision and recall. After considering the possible alternatives that would provide an aggregated, fast, full text search of a variety of data sources and file formats we decided to use Nutch [1] as a web crawler and Solr [2] as a search engine. To present XML-based Solr search results in a user-friendly format we use Drupal [3] as a web interface to Solr. We describe the experience of building a federated search for a heterogeneous collection of 10 million PHENIX documents with Nutch, Solr and Drupal.

MassSieve: Panning MS/MS peptide data for proteins

PubMed Central

Slotta, Douglas J.; McFarland, Melinda A.; Markey, Sanford P.

2010-01-01

We present MassSieve, a Java-based platform for visualization and parsimony analysis of single and comparative LC-MS/MS database search engine results. The success of mass spectrometric peptide sequence assignment algorithms has led to the need for a tool to merge and evaluate the increasing data set sizes that result from LC-MS/MS-based shotgun proteomic experiments. MassSieve supports reports from multiple search engines with differing search characteristics, which can increase peptide sequence coverage and/or identify conflicting or ambiguous spectral assignments. PMID:20564260

A comparison of Boolean-based retrieval to the WAIS system for retrieval of aeronautical information

NASA Technical Reports Server (NTRS)

Marchionini, Gary; Barlow, Diane

1994-01-01

An evaluation of an information retrieval system using a Boolean-based retrieval engine and inverted file architecture and WAIS, which uses a vector-based engine, was conducted. Four research questions in aeronautical engineering were used to retrieve sets of citations from the NASA Aerospace Database which was mounted on a WAIS server and available through Dialog File 108 which served as the Boolean-based system (BBS). High recall and high precision searches were done in the BBS and terse and verbose queries were used in the WAIS condition. Precision values for the WAIS searches were consistently above the precision values for high recall BBS searches and consistently below the precision values for high precision BBS searches. Terse WAIS queries gave somewhat better precision performance than verbose WAIS queries. In every case, a small number of relevant documents retrieved by one system were not retrieved by the other, indicating the incomplete nature of the results from either retrieval system. Relevant documents in the WAIS searches were found to be randomly distributed in the retrieved sets rather than distributed by ranks. Advantages and limitations of both types of systems are discussed.

A comparison of two search methods for determining the scope of systematic reviews and health technology assessments.

PubMed

Forsetlund, Louise; Kirkehei, Ingvild; Harboe, Ingrid; Odgaard-Jensen, Jan

2012-01-01

This study aims to compare two different search methods for determining the scope of a requested systematic review or health technology assessment. The first method (called the Direct Search Method) included performing direct searches in the Cochrane Database of Systematic Reviews (CDSR), Database of Abstracts of Reviews of Effects (DARE) and the Health Technology Assessments (HTA). Using the comparison method (called the NHS Search Engine) we performed searches by means of the search engine of the British National Health Service, NHS Evidence. We used an adapted cross-over design with a random allocation of fifty-five requests for systematic reviews. The main analyses were based on repeated measurements adjusted for the order in which the searches were conducted. The Direct Search Method generated on average fewer hits (48 percent [95 percent confidence interval {CI} 6 percent to 72 percent], had a higher precision (0.22 [95 percent CI, 0.13 to 0.30]) and more unique hits than when searching by means of the NHS Search Engine (50 percent [95 percent CI, 7 percent to 110 percent]). On the other hand, the Direct Search Method took longer (14.58 minutes [95 percent CI, 7.20 to 21.97]) and was perceived as somewhat less user-friendly than the NHS Search Engine (-0.60 [95 percent CI, -1.11 to -0.09]). Although the Direct Search Method had some drawbacks such as being more time-consuming and less user-friendly, it generated more unique hits than the NHS Search Engine, retrieved on average fewer references and fewer irrelevant results.

SearchGUI: A Highly Adaptable Common Interface for Proteomics Search and de Novo Engines.

PubMed

Barsnes, Harald; Vaudel, Marc

2018-05-25

Mass-spectrometry-based proteomics has become the standard approach for identifying and quantifying proteins. A vital step consists of analyzing experimentally generated mass spectra to identify the underlying peptide sequences for later mapping to the originating proteins. We here present the latest developments in SearchGUI, a common open-source interface for the most frequently used freely available proteomics search and de novo engines that has evolved into a central component in numerous bioinformatics workflows.

Usability evaluation of an experimental text summarization system and three search engines: implications for the reengineering of health care interfaces.

PubMed

Kushniruk, Andre W; Kan, Min-Yem; McKeown, Kathleen; Klavans, Judith; Jordan, Desmond; LaFlamme, Mark; Patel, Vimia L

2002-01-01

This paper describes the comparative evaluation of an experimental automated text summarization system, Centrifuser and three conventional search engines - Google, Yahoo and About.com. Centrifuser provides information to patients and families relevant to their questions about specific health conditions. It then produces a multidocument summary of articles retrieved by a standard search engine, tailored to the user's question. Subjects, consisting of friends or family of hospitalized patients, were asked to "think aloud" as they interacted with the four systems. The evaluation involved audio- and video recording of subject interactions with the interfaces in situ at a hospital. Results of the evaluation show that subjects found Centrifuser's summarization capability useful and easy to understand. In comparing Centrifuser to the three search engines, subjects' ratings varied; however, specific interface features were deemed useful across interfaces. We conclude with a discussion of the implications for engineering Web-based retrieval systems.

Chemical-text hybrid search engines.

PubMed

Zhou, Yingyao; Zhou, Bin; Jiang, Shumei; King, Frederick J

2010-01-01

As the amount of chemical literature increases, it is critical that researchers be enabled to accurately locate documents related to a particular aspect of a given compound. Existing solutions, based on text and chemical search engines alone, suffer from the inclusion of "false negative" and "false positive" results, and cannot accommodate diverse repertoire of formats currently available for chemical documents. To address these concerns, we developed an approach called Entity-Canonical Keyword Indexing (ECKI), which converts a chemical entity embedded in a data source into its canonical keyword representation prior to being indexed by text search engines. We implemented ECKI using Microsoft Office SharePoint Server Search, and the resultant hybrid search engine not only supported complex mixed chemical and keyword queries but also was applied to both intranet and Internet environments. We envision that the adoption of ECKI will empower researchers to pose more complex search questions that were not readily attainable previously and to obtain answers at much improved speed and accuracy.

Optimizing Online Suicide Prevention: A Search Engine-Based Tailored Approach.

PubMed

Arendt, Florian; Scherr, Sebastian

2017-11-01

Search engines are increasingly used to seek suicide-related information online, which can serve both harmful and helpful purposes. Google acknowledges this fact and presents a suicide-prevention result for particular search terms. Unfortunately, the result is only presented to a limited number of visitors. Hence, Google is missing the opportunity to provide help to vulnerable people. We propose a two-step approach to a tailored optimization: First, research will identify the risk factors. Second, search engines will reweight algorithms according to the risk factors. In this study, we show that the query share of the search term "poisoning" on Google shows substantial peaks corresponding to peaks in actual suicidal behavior. Accordingly, thresholds for showing the suicide-prevention result should be set to the lowest levels during the spring, on Sundays and Mondays, on New Year's Day, and on Saturdays following Thanksgiving. Search engines can help to save lives globally by utilizing a more tailored approach to suicide prevention.

Concept Mapping Your Web Searches: A Design Rationale and Web-Enabled Application

ERIC Educational Resources Information Center

Lee, Y.-J.

2004-01-01

Although it has become very common to use World Wide Web-based information in many educational settings, there has been little research on how to better search and organize Web-based information. This paper discusses the shortcomings of Web search engines and Web browsers as learning environments and describes an alternative Web search environment…

Phenotip - a web-based instrument to help diagnosing fetal syndromes antenatally.

PubMed

Porat, Shay; de Rham, Maud; Giamboni, Davide; Van Mieghem, Tim; Baud, David

2014-12-10

Prenatal ultrasound can often reliably distinguish fetal anatomic anomalies, particularly in the hands of an experienced ultrasonographer. Given the large number of existing syndromes and the significant overlap in prenatal findings, antenatal differentiation for syndrome diagnosis is difficult. We constructed a hierarchic tree of 1140 sonographic markers and submarkers, organized per organ system. Subsequently, a database of prenatally diagnosable syndromes was built. An internet-based search engine was then designed to search the syndrome database based on a single or multiple sonographic markers. Future developments will include a database with magnetic resonance imaging findings as well as further refinements in the search engine to allow prioritization based on incidence of syndromes and markers.

GoWeb: a semantic search engine for the life science web.

PubMed

Dietze, Heiko; Schroeder, Michael

2009-10-01

Current search engines are keyword-based. Semantic technologies promise a next generation of semantic search engines, which will be able to answer questions. Current approaches either apply natural language processing to unstructured text or they assume the existence of structured statements over which they can reason. Here, we introduce a third approach, GoWeb, which combines classical keyword-based Web search with text-mining and ontologies to navigate large results sets and facilitate question answering. We evaluate GoWeb on three benchmarks of questions on genes and functions, on symptoms and diseases, and on proteins and diseases. The first benchmark is based on the BioCreAtivE 1 Task 2 and links 457 gene names with 1352 functions. GoWeb finds 58% of the functional GeneOntology annotations. The second benchmark is based on 26 case reports and links symptoms with diseases. GoWeb achieves 77% success rate improving an existing approach by nearly 20%. The third benchmark is based on 28 questions in the TREC genomics challenge and links proteins to diseases. GoWeb achieves a success rate of 79%. GoWeb's combination of classical Web search with text-mining and ontologies is a first step towards answering questions in the biomedical domain. GoWeb is online at: http://www.gopubmed.org/goweb.

Creative Engineering Based Education with Autonomous Robots Considering Job Search Support

NASA Astrophysics Data System (ADS)

Takezawa, Satoshi; Nagamatsu, Masao; Takashima, Akihiko; Nakamura, Kaeko; Ohtake, Hideo; Yoshida, Kanou

The Robotics Course in our Mechanical Systems Engineering Department offers “Robotics Exercise Lessons” as one of its Problem-Solution Based Specialized Subjects. This is intended to motivate students learning and to help them acquire fundamental items and skills on mechanical engineering and improve understanding of Robotics Basic Theory. Our current curriculum was established to accomplish this objective based on two pieces of research in 2005: an evaluation questionnaire on the education of our Mechanical Systems Engineering Department for graduates and a survey on the kind of human resources which companies are seeking and their expectations for our department. This paper reports the academic results and reflections of job search support in recent years as inherited and developed from the previous curriculum.

Quality analysis of patient information about knee arthroscopy on the World Wide Web.

PubMed

Sambandam, Senthil Nathan; Ramasamy, Vijayaraj; Priyanka, Priyanka; Ilango, Balakrishnan

2007-05-01

This study was designed to ascertain the quality of patient information available on the World Wide Web on the topic of knee arthroscopy. For the purpose of quality analysis, we used a pool of 232 search results obtained from 7 different search engines. We used a modified assessment questionnaire to assess the quality of these Web sites. This questionnaire was developed based on similar studies evaluating Web site quality and includes items on illustrations, accessibility, availability, accountability, and content of the Web site. We also compared results obtained with different search engines and tried to establish the best possible search strategy to attain the most relevant, authentic, and adequate information with minimum time consumption. For this purpose, we first compared 100 search results from the single most commonly used search engine (AltaVista) with the pooled sample containing 20 search results from each of the 7 different search engines. The search engines used were metasearch (Copernic and Mamma), general search (Google, AltaVista, and Yahoo), and health topic-related search engines (MedHunt and Healthfinder). The phrase "knee arthroscopy" was used as the search terminology. Excluding the repetitions, there were 117 Web sites available for quality analysis. These sites were analyzed for accessibility, relevance, authenticity, adequacy, and accountability by use of a specially designed questionnaire. Our analysis showed that most of the sites providing patient information on knee arthroscopy contained outdated information, were inadequate, and were not accountable. Only 16 sites were found to be providing reasonably good patient information and hence can be recommended to patients. Understandably, most of these sites were from nonprofit organizations and educational institutions. Furthermore, our study revealed that using multiple search engines increases patients' chances of obtaining more relevant information rather than using a single search engine. Our study shows the difficulties encountered by patients in obtaining information regarding knee arthroscopy and highlights the duty of knee surgeons in helping patients to identify the relevant and authentic information in the most efficient manner from the World Wide Web. This study highlights the importance of the role of orthopaedic surgeons in helping their patients to identify the best possible information on the World Wide Web.

Web Feet Guide to Search Engines: Finding It on the Net.

ERIC Educational Resources Information Center

Web Feet, 2001

2001-01-01

This guide to search engines for the World Wide Web discusses selecting the right search engine; interpreting search results; major search engines; online tutorials and guides; search engines for kids; specialized search tools for various subjects; and other specialized engines and gateways. (LRW)

Development and tuning of an original search engine for patent libraries in medicinal chemistry.

PubMed

Pasche, Emilie; Gobeill, Julien; Kreim, Olivier; Oezdemir-Zaech, Fatma; Vachon, Therese; Lovis, Christian; Ruch, Patrick

2014-01-01

The large increase in the size of patent collections has led to the need of efficient search strategies. But the development of advanced text-mining applications dedicated to patents of the biomedical field remains rare, in particular to address the needs of the pharmaceutical & biotech industry, which intensively uses patent libraries for competitive intelligence and drug development. We describe here the development of an advanced retrieval engine to search information in patent collections in the field of medicinal chemistry. We investigate and combine different strategies and evaluate their respective impact on the performance of the search engine applied to various search tasks, which covers the putatively most frequent search behaviours of intellectual property officers in medical chemistry: 1) a prior art search task; 2) a technical survey task; and 3) a variant of the technical survey task, sometimes called known-item search task, where a single patent is targeted. The optimal tuning of our engine resulted in a top-precision of 6.76% for the prior art search task, 23.28% for the technical survey task and 46.02% for the variant of the technical survey task. We observed that co-citation boosting was an appropriate strategy to improve prior art search tasks, while IPC classification of queries was improving retrieval effectiveness for technical survey tasks. Surprisingly, the use of the full body of the patent was always detrimental for search effectiveness. It was also observed that normalizing biomedical entities using curated dictionaries had simply no impact on the search tasks we evaluate. The search engine was finally implemented as a web-application within Novartis Pharma. The application is briefly described in the report. We have presented the development of a search engine dedicated to patent search, based on state of the art methods applied to patent corpora. We have shown that a proper tuning of the system to adapt to the various search tasks clearly increases the effectiveness of the system. We conclude that different search tasks demand different information retrieval engines' settings in order to yield optimal end-user retrieval.

Development and tuning of an original search engine for patent libraries in medicinal chemistry

PubMed Central

2014-01-01

Background The large increase in the size of patent collections has led to the need of efficient search strategies. But the development of advanced text-mining applications dedicated to patents of the biomedical field remains rare, in particular to address the needs of the pharmaceutical & biotech industry, which intensively uses patent libraries for competitive intelligence and drug development. Methods We describe here the development of an advanced retrieval engine to search information in patent collections in the field of medicinal chemistry. We investigate and combine different strategies and evaluate their respective impact on the performance of the search engine applied to various search tasks, which covers the putatively most frequent search behaviours of intellectual property officers in medical chemistry: 1) a prior art search task; 2) a technical survey task; and 3) a variant of the technical survey task, sometimes called known-item search task, where a single patent is targeted. Results The optimal tuning of our engine resulted in a top-precision of 6.76% for the prior art search task, 23.28% for the technical survey task and 46.02% for the variant of the technical survey task. We observed that co-citation boosting was an appropriate strategy to improve prior art search tasks, while IPC classification of queries was improving retrieval effectiveness for technical survey tasks. Surprisingly, the use of the full body of the patent was always detrimental for search effectiveness. It was also observed that normalizing biomedical entities using curated dictionaries had simply no impact on the search tasks we evaluate. The search engine was finally implemented as a web-application within Novartis Pharma. The application is briefly described in the report. Conclusions We have presented the development of a search engine dedicated to patent search, based on state of the art methods applied to patent corpora. We have shown that a proper tuning of the system to adapt to the various search tasks clearly increases the effectiveness of the system. We conclude that different search tasks demand different information retrieval engines' settings in order to yield optimal end-user retrieval. PMID:24564220

Adaptation of Decoy Fusion Strategy for Existing Multi-Stage Search Workflows

NASA Astrophysics Data System (ADS)

Ivanov, Mark V.; Levitsky, Lev I.; Gorshkov, Mikhail V.

2016-09-01

A number of proteomic database search engines implement multi-stage strategies aiming at increasing the sensitivity of proteome analysis. These approaches often employ a subset of the original database for the secondary stage of analysis. However, if target-decoy approach (TDA) is used for false discovery rate (FDR) estimation, the multi-stage strategies may violate the underlying assumption of TDA that false matches are distributed uniformly across the target and decoy databases. This violation occurs if the numbers of target and decoy proteins selected for the second search are not equal. Here, we propose a method of decoy database generation based on the previously reported decoy fusion strategy. This method allows unbiased TDA-based FDR estimation in multi-stage searches and can be easily integrated into existing workflows utilizing popular search engines and post-search algorithms.

‘Sciencenet’—towards a global search and share engine for all scientific knowledge

PubMed Central

Lütjohann, Dominic S.; Shah, Asmi H.; Christen, Michael P.; Richter, Florian; Knese, Karsten; Liebel, Urban

2011-01-01

Summary: Modern biological experiments create vast amounts of data which are geographically distributed. These datasets consist of petabytes of raw data and billions of documents. Yet to the best of our knowledge, a search engine technology that searches and cross-links all different data types in life sciences does not exist. We have developed a prototype distributed scientific search engine technology, ‘Sciencenet’, which facilitates rapid searching over this large data space. By ‘bringing the search engine to the data’, we do not require server farms. This platform also allows users to contribute to the search index and publish their large-scale data to support e-Science. Furthermore, a community-driven method guarantees that only scientific content is crawled and presented. Our peer-to-peer approach is sufficiently scalable for the science web without performance or capacity tradeoff. Availability and Implementation: The free to use search portal web page and the downloadable client are accessible at: http://sciencenet.kit.edu. The web portal for index administration is implemented in ASP.NET, the ‘AskMe’ experiment publisher is written in Python 2.7, and the backend ‘YaCy’ search engine is based on Java 1.6. Contact: urban.liebel@kit.edu Supplementary Material: Detailed instructions and descriptions can be found on the project homepage: http://sciencenet.kit.edu. PMID:21493657

reSpect: Software for Identification of High and Low Abundance Ion Species in Chimeric Tandem Mass Spectra

PubMed Central

Shteynberg, David; Mendoza, Luis; Hoopmann, Michael R.; Sun, Zhi; Schmidt, Frank; Deutsch, Eric W.; Moritz, Robert L.

2016-01-01

Most shotgun proteomics data analysis workflows are based on the assumption that each fragment ion spectrum is explained by a single species of peptide ion isolated by the mass spectrometer; however, in reality mass spectrometers often isolate more than one peptide ion within the window of isolation that contributes to additional peptide fragment peaks in many spectra. We present a new tool called reSpect, implemented in the Trans-Proteomic Pipeline (TPP), that enables an iterative workflow whereby fragment ion peaks explained by a peptide ion identified in one round of sequence searching or spectral library search are attenuated based on the confidence of the identification, and then the altered spectrum is subjected to further rounds of searching. The reSpect tool is not implemented as a search engine, but rather as a post search engine processing step where only fragment ion intensities are altered. This enables the application of any search engine combination in the following iterations. Thus, reSpect is compatible with all other protein sequence database search engines as well as peptide spectral library search engines that are supported by the TPP. We show that while some datasets are highly amenable to chimeric spectrum identification and lead to additional peptide identification boosts of over 30% with as many as four different peptide ions identified per spectrum, datasets with narrow precursor ion selection only benefit from such processing at the level of a few percent. We demonstrate a technique that facilitates the determination of the degree to which a dataset would benefit from chimeric spectrum analysis. The reSpect tool is free and open source, provided within the TPP and available at the TPP website. PMID:26419769

reSpect: software for identification of high and low abundance ion species in chimeric tandem mass spectra.

PubMed

Shteynberg, David; Mendoza, Luis; Hoopmann, Michael R; Sun, Zhi; Schmidt, Frank; Deutsch, Eric W; Moritz, Robert L

2015-11-01

Most shotgun proteomics data analysis workflows are based on the assumption that each fragment ion spectrum is explained by a single species of peptide ion isolated by the mass spectrometer; however, in reality mass spectrometers often isolate more than one peptide ion within the window of isolation that contribute to additional peptide fragment peaks in many spectra. We present a new tool called reSpect, implemented in the Trans-Proteomic Pipeline (TPP), which enables an iterative workflow whereby fragment ion peaks explained by a peptide ion identified in one round of sequence searching or spectral library search are attenuated based on the confidence of the identification, and then the altered spectrum is subjected to further rounds of searching. The reSpect tool is not implemented as a search engine, but rather as a post-search engine processing step where only fragment ion intensities are altered. This enables the application of any search engine combination in the iterations that follow. Thus, reSpect is compatible with all other protein sequence database search engines as well as peptide spectral library search engines that are supported by the TPP. We show that while some datasets are highly amenable to chimeric spectrum identification and lead to additional peptide identification boosts of over 30% with as many as four different peptide ions identified per spectrum, datasets with narrow precursor ion selection only benefit from such processing at the level of a few percent. We demonstrate a technique that facilitates the determination of the degree to which a dataset would benefit from chimeric spectrum analysis. The reSpect tool is free and open source, provided within the TPP and available at the TPP website. Graphical Abstract ᅟ.

reSpect: Software for Identification of High and Low Abundance Ion Species in Chimeric Tandem Mass Spectra

NASA Astrophysics Data System (ADS)

Shteynberg, David; Mendoza, Luis; Hoopmann, Michael R.; Sun, Zhi; Schmidt, Frank; Deutsch, Eric W.; Moritz, Robert L.

2015-11-01

Most shotgun proteomics data analysis workflows are based on the assumption that each fragment ion spectrum is explained by a single species of peptide ion isolated by the mass spectrometer; however, in reality mass spectrometers often isolate more than one peptide ion within the window of isolation that contribute to additional peptide fragment peaks in many spectra. We present a new tool called reSpect, implemented in the Trans-Proteomic Pipeline (TPP), which enables an iterative workflow whereby fragment ion peaks explained by a peptide ion identified in one round of sequence searching or spectral library search are attenuated based on the confidence of the identification, and then the altered spectrum is subjected to further rounds of searching. The reSpect tool is not implemented as a search engine, but rather as a post-search engine processing step where only fragment ion intensities are altered. This enables the application of any search engine combination in the iterations that follow. Thus, reSpect is compatible with all other protein sequence database search engines as well as peptide spectral library search engines that are supported by the TPP. We show that while some datasets are highly amenable to chimeric spectrum identification and lead to additional peptide identification boosts of over 30% with as many as four different peptide ions identified per spectrum, datasets with narrow precursor ion selection only benefit from such processing at the level of a few percent. We demonstrate a technique that facilitates the determination of the degree to which a dataset would benefit from chimeric spectrum analysis. The reSpect tool is free and open source, provided within the TPP and available at the TPP website.

Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine.

PubMed

Hanauer, David A; Wu, Danny T Y; Yang, Lei; Mei, Qiaozhu; Murkowski-Steffy, Katherine B; Vydiswaran, V G Vinod; Zheng, Kai

2017-03-01

The utility of biomedical information retrieval environments can be severely limited when users lack expertise in constructing effective search queries. To address this issue, we developed a computer-based query recommendation algorithm that suggests semantically interchangeable terms based on an initial user-entered query. In this study, we assessed the value of this approach, which has broad applicability in biomedical information retrieval, by demonstrating its application as part of a search engine that facilitates retrieval of information from electronic health records (EHRs). The query recommendation algorithm utilizes MetaMap to identify medical concepts from search queries and indexed EHR documents. Synonym variants from UMLS are used to expand the concepts along with a synonym set curated from historical EHR search logs. The empirical study involved 33 clinicians and staff who evaluated the system through a set of simulated EHR search tasks. User acceptance was assessed using the widely used technology acceptance model. The search engine's performance was rated consistently higher with the query recommendation feature turned on vs. off. The relevance of computer-recommended search terms was also rated high, and in most cases the participants had not thought of these terms on their own. The questions on perceived usefulness and perceived ease of use received overwhelmingly positive responses. A vast majority of the participants wanted the query recommendation feature to be available to assist in their day-to-day EHR search tasks. Challenges persist for users to construct effective search queries when retrieving information from biomedical documents including those from EHRs. This study demonstrates that semantically-based query recommendation is a viable solution to addressing this challenge. Published by Elsevier Inc.

iPixel: a visual content-based and semantic search engine for retrieving digitized mammograms by using collective intelligence.

PubMed

Alor-Hernández, Giner; Pérez-Gallardo, Yuliana; Posada-Gómez, Rubén; Cortes-Robles, Guillermo; Rodríguez-González, Alejandro; Aguilar-Laserre, Alberto A

2012-09-01

Nowadays, traditional search engines such as Google, Yahoo and Bing facilitate the retrieval of information in the format of images, but the results are not always useful for the users. This is mainly due to two problems: (1) the semantic keywords are not taken into consideration and (2) it is not always possible to establish a query using the image features. This issue has been covered in different domains in order to develop content-based image retrieval (CBIR) systems. The expert community has focussed their attention on the healthcare domain, where a lot of visual information for medical analysis is available. This paper provides a solution called iPixel Visual Search Engine, which involves semantics and content issues in order to search for digitized mammograms. iPixel offers the possibility of retrieving mammogram features using collective intelligence and implementing a CBIR algorithm. Our proposal compares not only features with similar semantic meaning, but also visual features. In this sense, the comparisons are made in different ways: by the number of regions per image, by maximum and minimum size of regions per image and by average intensity level of each region. iPixel Visual Search Engine supports the medical community in differential diagnoses related to the diseases of the breast. The iPixel Visual Search Engine has been validated by experts in the healthcare domain, such as radiologists, in addition to experts in digital image analysis.

Preliminary comparison of the Essie and PubMed search engines for answering clinical questions using MD on Tap, a PDA-based program for accessing biomedical literature.

PubMed

Sutton, Victoria R; Hauser, Susan E

2005-01-01

MD on Tap, a PDA application that searches and retrieves biomedical literature, is specifically designed for use by mobile healthcare professionals. With the goal of improving the usability of the application, a preliminary comparison was made of two search engines (PubMed and Essie) to determine which provided most efficient path to the desired clinically-relevant information.

The Role of Exploratory Talk in Classroom Search Engine Tasks

ERIC Educational Resources Information Center

Knight, Simon; Mercer, Neil

2015-01-01

While search engines are commonly used by children to find information, and in classroom-based activities, children are not adept in their information seeking or evaluation of information sources. Prior work has explored such activities in isolated, individual contexts, failing to account for the collaborative, discourse-mediated nature of search…

www.teld.net: Online Courseware Engine for Teaching by Examples and Learning by Doing.

ERIC Educational Resources Information Center

Huang, G. Q.; Shen, B.; Mak, K. L.

2001-01-01

Describes TELD (Teaching by Examples and Learning by Doing), a Web-based online courseware engine for higher education. Topics include problem-based learning; project-based learning; case methods; TELD as a Web server; course materials; TELD as a search engine; and TELD as an online virtual classroom for electronic delivery of electronic…

Finding and Exploring Health Information with a Slider-Based User Interface.

PubMed

Pang, Patrick Cheong-Iao; Verspoor, Karin; Pearce, Jon; Chang, Shanton

2016-01-01

Despite the fact that search engines are the primary channel to access online health information, there are better ways to find and explore health information on the web. Search engines are prone to problems when they are used to find health information. For instance, users have difficulties in expressing health scenarios with appropriate search keywords, search results are not optimised for medical queries, and the search process does not account for users' literacy levels and reading preferences. In this paper, we describe our approach to addressing these problems by introducing a novel design using a slider-based user interface for discovering health information without the need for precise search keywords. The user evaluation suggests that the interface is easy to use and able to assist users in the process of discovering new information. This study demonstrates the potential value of adopting slider controls in the user interface of health websites for navigation and information discovery.

Searching the scientific literature: implications for quantitative and qualitative reviews.

PubMed

Wu, Yelena P; Aylward, Brandon S; Roberts, Michael C; Evans, Spencer C

2012-08-01

Literature reviews are an essential step in the research process and are included in all empirical and review articles. Electronic databases are commonly used to gather this literature. However, several factors can affect the extent to which relevant articles are retrieved, influencing future research and conclusions drawn. The current project examined articles obtained by comparable search strategies in two electronic archives using an exemplar search to illustrate factors that authors should consider when designing their own search strategies. Specifically, literature searches were conducted in PsycINFO and PubMed targeting review articles on two exemplar disorders (bipolar disorder and attention deficit/hyperactivity disorder) and issues of classification and/or differential diagnosis. Articles were coded for relevance and characteristics of article content. The two search engines yielded significantly different proportions of relevant articles overall and by disorder. Keywords differed across search engines for the relevant articles identified. Based on these results, it is recommended that when gathering literature for review papers, multiple search engines should be used, and search syntax and strategies be tailored to the unique capabilities of particular engines. For meta-analyses and systematic reviews, authors may consider reporting the extent to which different archives or sources yielded relevant articles for their particular review. Copyright © 2012 Elsevier Ltd. All rights reserved.

Specialized medical search-engines are no better than general search-engines in sourcing consumer information about androgen deficiency.

PubMed

Ilic, D; Bessell, T L; Silagy, C A; Green, S

2003-03-01

The Internet provides consumers with access to online health information; however, identifying relevant and valid information can be problematic. Our objectives were firstly to investigate the efficiency of search-engines, and then to assess the quality of online information pertaining to androgen deficiency in the ageing male (ADAM). Keyword searches were performed on nine search-engines (four general and five medical) to identify website information regarding ADAM. Search-engine efficiency was compared by percentage of relevant websites obtained via each search-engine. The quality of information published on each website was assessed using the DISCERN rating tool. Of 4927 websites searched, 47 (1.44%) and 10 (0.60%) relevant websites were identified by general and medical search-engines respectively. The overall quality of online information on ADAM was poor. The quality of websites retrieved using medical search-engines did not differ significantly from those retrieved by general search-engines. Despite the poor quality of online information relating to ADAM, it is evident that medical search-engines are no better than general search-engines in sourcing consumer information relevant to ADAM.

Electronic Biomedical Literature Search for Budding Researcher

PubMed Central

Thakre, Subhash B.; Thakre S, Sushama S.; Thakre, Amol D.

2013-01-01

Search for specific and well defined literature related to subject of interest is the foremost step in research. When we are familiar with topic or subject then we can frame appropriate research question. Appropriate research question is the basis for study objectives and hypothesis. The Internet provides a quick access to an overabundance of the medical literature, in the form of primary, secondary and tertiary literature. It is accessible through journals, databases, dictionaries, textbooks, indexes, and e-journals, thereby allowing access to more varied, individualised, and systematic educational opportunities. Web search engine is a tool designed to search for information on the World Wide Web, which may be in the form of web pages, images, information, and other types of files. Search engines for internet-based search of medical literature include Google, Google scholar, Scirus, Yahoo search engine, etc., and databases include MEDLINE, PubMed, MEDLARS, etc. Several web-libraries (National library Medicine, Cochrane, Web of Science, Medical matrix, Emory libraries) have been developed as meta-sites, providing useful links to health resources globally. A researcher must keep in mind the strengths and limitations of a particular search engine/database while searching for a particular type of data. Knowledge about types of literature, levels of evidence, and detail about features of search engine as available, user interface, ease of access, reputable content, and period of time covered allow their optimal use and maximal utility in the field of medicine. Literature search is a dynamic and interactive process; there is no one way to conduct a search and there are many variables involved. It is suggested that a systematic search of literature that uses available electronic resource effectively, is more likely to produce quality research. PMID:24179937

Electronic biomedical literature search for budding researcher.

PubMed

Thakre, Subhash B; Thakre S, Sushama S; Thakre, Amol D

2013-09-01

Search for specific and well defined literature related to subject of interest is the foremost step in research. When we are familiar with topic or subject then we can frame appropriate research question. Appropriate research question is the basis for study objectives and hypothesis. The Internet provides a quick access to an overabundance of the medical literature, in the form of primary, secondary and tertiary literature. It is accessible through journals, databases, dictionaries, textbooks, indexes, and e-journals, thereby allowing access to more varied, individualised, and systematic educational opportunities. Web search engine is a tool designed to search for information on the World Wide Web, which may be in the form of web pages, images, information, and other types of files. Search engines for internet-based search of medical literature include Google, Google scholar, Scirus, Yahoo search engine, etc., and databases include MEDLINE, PubMed, MEDLARS, etc. Several web-libraries (National library Medicine, Cochrane, Web of Science, Medical matrix, Emory libraries) have been developed as meta-sites, providing useful links to health resources globally. A researcher must keep in mind the strengths and limitations of a particular search engine/database while searching for a particular type of data. Knowledge about types of literature, levels of evidence, and detail about features of search engine as available, user interface, ease of access, reputable content, and period of time covered allow their optimal use and maximal utility in the field of medicine. Literature search is a dynamic and interactive process; there is no one way to conduct a search and there are many variables involved. It is suggested that a systematic search of literature that uses available electronic resource effectively, is more likely to produce quality research.

Preliminary comparison of the Essie and PubMed search engines for answering clinical questions using MD on Tap, a PDA-based program for accessing biomedical literature

PubMed Central

Sutton, Victoria R.; Hauser, Susan E.

2005-01-01

MD on Tap, a PDA application that searches and retrieves biomedical literature, is specifically designed for use by mobile healthcare professionals. With the goal of improving the usability of the application, a preliminary comparison was made of two search engines (PubMed and Essie) to determine which provided most efficient path to the desired clinically-relevant information. PMID:16779415

Directing the public to evidence-based online content.

PubMed

Cooper, Crystale Purvis; Gelb, Cynthia A; Vaughn, Alexandra N; Smuland, Jenny; Hughes, Alexandra G; Hawkins, Nikki A

2015-04-01

To direct online users searching for gynecologic cancer information to accurate content, the Centers for Disease Control and Prevention's (CDC) 'Inside Knowledge: Get the Facts About Gynecologic Cancer' campaign sponsored search engine advertisements in English and Spanish. From June 2012 to August 2013, advertisements appeared when US Google users entered search terms related to gynecologic cancer. Users who clicked on the advertisements were directed to relevant content on the CDC website. Compared with the 3 months before the initiative (March-May 2012), visits to the CDC web pages linked to the advertisements were 26 times higher after the initiative began (June-August 2012) (p<0.01), and 65 times higher when the search engine advertisements were supplemented with promotion on television and additional websites (September 2012-August 2013) (p<0.01). Search engine advertisements can direct users to evidence-based content at a highly teachable moment--when they are seeking relevant information. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Context-Aware Online Commercial Intention Detection

NASA Astrophysics Data System (ADS)

Hu, Derek Hao; Shen, Dou; Sun, Jian-Tao; Yang, Qiang; Chen, Zheng

With more and more commercial activities moving onto the Internet, people tend to purchase what they need through Internet or conduct some online research before the actual transactions happen. For many Web users, their online commercial activities start from submitting a search query to search engines. Just like the common Web search queries, the queries with commercial intention are usually very short. Recognizing the queries with commercial intention against the common queries will help search engines provide proper search results and advertisements, help Web users obtain the right information they desire and help the advertisers benefit from the potential transactions. However, the intentions behind a query vary a lot for users with different background and interest. The intentions can even be different for the same user, when the query is issued in different contexts. In this paper, we present a new algorithm framework based on skip-chain conditional random field (SCCRF) for automatically classifying Web queries according to context-based online commercial intention. We analyze our algorithm performance both theoretically and empirically. Extensive experiments on several real search engine log datasets show that our algorithm can improve more than 10% on F1 score than previous algorithms on commercial intention detection.

Adjacency and Proximity Searching in the Science Citation Index and Google

DTIC Science & Technology

2005-01-01

major database search engines , including commercial S&T database search engines (e.g., Science Citation Index (SCI), Engineering Compendex (EC...PubMed, OVID), Federal agency award database search engines (e.g., NSF, NIH, DOE, EPA, as accessed in Federal R&D Project Summaries), Web search Engines (e.g...searching. Some database search engines allow strict constrained co- occurrence searching as a user option (e.g., OVID, EC), while others do not (e.g., SCI

Start Your Engines: Surfing with Search Engines for Kids.

ERIC Educational Resources Information Center

Byerly, Greg; Brodie, Carolyn S.

1999-01-01

Suggests that to be an effective educator and user of the Web it is essential to know the basics about search engines. Presents tips for using search engines. Describes several search engines for children and young adults, as well as some general filtered search engines for children. (AEF)

(Meta)Search like Google

ERIC Educational Resources Information Center

Rochkind, Jonathan

2007-01-01

The ability to search and receive results in more than one database through a single interface--or metasearch--is something many users want. Google Scholar--the search engine of specifically scholarly content--and library metasearch products like Ex Libris's MetaLib, Serials Solution's Central Search, WebFeat, and products based on MuseGlobal used…

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy datasets. From the study and discussion with NASA LERC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.

A novel algorithm for validating peptide identification from a shotgun proteomics search engine.

PubMed

Jian, Ling; Niu, Xinnan; Xia, Zhonghang; Samir, Parimal; Sumanasekera, Chiranthani; Mu, Zheng; Jennings, Jennifer L; Hoek, Kristen L; Allos, Tara; Howard, Leigh M; Edwards, Kathryn M; Weil, P Anthony; Link, Andrew J

2013-03-01

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has revolutionized the proteomics analysis of complexes, cells, and tissues. In a typical proteomic analysis, the tandem mass spectra from a LC-MS/MS experiment are assigned to a peptide by a search engine that compares the experimental MS/MS peptide data to theoretical peptide sequences in a protein database. The peptide spectra matches are then used to infer a list of identified proteins in the original sample. However, the search engines often fail to distinguish between correct and incorrect peptides assignments. In this study, we designed and implemented a novel algorithm called De-Noise to reduce the number of incorrect peptide matches and maximize the number of correct peptides at a fixed false discovery rate using a minimal number of scoring outputs from the SEQUEST search engine. The novel algorithm uses a three-step process: data cleaning, data refining through a SVM-based decision function, and a final data refining step based on proteolytic peptide patterns. Using proteomics data generated on different types of mass spectrometers, we optimized the De-Noise algorithm on the basis of the resolution and mass accuracy of the mass spectrometer employed in the LC-MS/MS experiment. Our results demonstrate De-Noise improves peptide identification compared to other methods used to process the peptide sequence matches assigned by SEQUEST. Because De-Noise uses a limited number of scoring attributes, it can be easily implemented with other search engines.

Diagnosis of Chronic Kidney Disease Based on Support Vector Machine by Feature Selection Methods.

PubMed

Polat, Huseyin; Danaei Mehr, Homay; Cetin, Aydin

2017-04-01

As Chronic Kidney Disease progresses slowly, early detection and effective treatment are the only cure to reduce the mortality rate. Machine learning techniques are gaining significance in medical diagnosis because of their classification ability with high accuracy rates. The accuracy of classification algorithms depend on the use of correct feature selection algorithms to reduce the dimension of datasets. In this study, Support Vector Machine classification algorithm was used to diagnose Chronic Kidney Disease. To diagnose the Chronic Kidney Disease, two essential types of feature selection methods namely, wrapper and filter approaches were chosen to reduce the dimension of Chronic Kidney Disease dataset. In wrapper approach, classifier subset evaluator with greedy stepwise search engine and wrapper subset evaluator with the Best First search engine were used. In filter approach, correlation feature selection subset evaluator with greedy stepwise search engine and filtered subset evaluator with the Best First search engine were used. The results showed that the Support Vector Machine classifier by using filtered subset evaluator with the Best First search engine feature selection method has higher accuracy rate (98.5%) in the diagnosis of Chronic Kidney Disease compared to other selected methods.

Adding a visualization feature to web search engines: it's time.

PubMed

Wong, Pak Chung

2008-01-01

It's widely recognized that all Web search engines today are almost identical in presentation layout and behavior. In fact, the same presentation approach has been applied to depicting search engine results pages (SERPs) since the first Web search engine launched in 1993. In this Visualization Viewpoints article, I propose to add a visualization feature to Web search engines and suggest that the new addition can improve search engines' performance and capabilities, which in turn lead to better Web search technology.

Web-based Electronic Sharing and RE-allocation of Assets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leverett, Dave; Miller, Robert A.; Berlin, Gary J.

2002-09-09

The Electronic Asses Sharing Program is a web-based application that provides the capability for complex-wide sharing and reallocation of assets that are excess, under utilized, or un-utilized. through a web-based fron-end and supporting has database with a search engine, users can search for assets that they need, search for assets needed by others, enter assets they need, and enter assets they have available for reallocation. In addition, entire listings of available assets and needed assets can be viewed. The application is written in Java, the hash database and search engine are in Object-oriented Java Database Management (OJDBM). The application willmore » be hosted on an SRS-managed server outside the Firewall and access will be controlled via a protected realm. An example of the application can be viewed at the followinig (temporary) URL: http://idgdev.srs.gov/servlet/srs.weshare.WeShare« less

Targeted exploration and analysis of large cross-platform human transcriptomic compendia

PubMed Central

Zhu, Qian; Wong, Aaron K; Krishnan, Arjun; Aure, Miriam R; Tadych, Alicja; Zhang, Ran; Corney, David C; Greene, Casey S; Bongo, Lars A; Kristensen, Vessela N; Charikar, Moses; Li, Kai; Troyanskaya, Olga G.

2016-01-01

We present SEEK (http://seek.princeton.edu), a query-based search engine across very large transcriptomic data collections, including thousands of human data sets from almost 50 microarray and next-generation sequencing platforms. SEEK uses a novel query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify query-coregulated genes, pathways, and processes. SEEK provides cross-platform handling, multi-gene query search, iterative metadata-based search refinement, and extensive visualization-based analysis options. PMID:25581801

75 FR 39285 - Tennessee Valley Authority; Notice of Receipt of Updated Antitrust Information and Opportunity...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-08

... either the Web-based search (advanced search) engine or the ADAMS find tool in Citrix. Within 30 days.... To search for other related documents in ADAMS using the Watts Bar Nuclear Plant Unit 2 OL...

Meta Search Engines.

ERIC Educational Resources Information Center

Garman, Nancy

1999-01-01

Describes common options and features to consider in evaluating which meta search engine will best meet a searcher's needs. Discusses number and names of engines searched; other sources and specialty engines; search queries; other search options; and results options. (AEF)

JournalMap: Research. Reimagined.

USDA-ARS?s Scientific Manuscript database

JournalMap is a scientific literature search engine that empowers you to find relevant research based on location and biophysical variables as well as traditional keyword searches. All publications are geotagged based on reported location information and plotted on a world map showing where the rese...

Decision making in family medicine: randomized trial of the effects of the InfoClinique and Trip database search engines.

PubMed

Labrecque, Michel; Ratté, Stéphane; Frémont, Pierre; Cauchon, Michel; Ouellet, Jérôme; Hogg, William; McGowan, Jessie; Gagnon, Marie-Pierre; Njoya, Merlin; Légaré, France

2013-10-01

To compare the ability of users of 2 medical search engines, InfoClinique and the Trip database, to provide correct answers to clinical questions and to explore the perceived effects of the tools on the clinical decision-making process. Randomized trial. Three family medicine units of the family medicine program of the Faculty of Medicine at Laval University in Quebec city, Que. Fifteen second-year family medicine residents. Residents generated 30 structured questions about therapy or preventive treatment (2 questions per resident) based on clinical encounters. Using an Internet platform designed for the trial, each resident answered 20 of these questions (their own 2, plus 18 of the questions formulated by other residents, selected randomly) before and after searching for information with 1 of the 2 search engines. For each question, 5 residents were randomly assigned to begin their search with InfoClinique and 5 with the Trip database. The ability of residents to provide correct answers to clinical questions using the search engines, as determined by third-party evaluation. After answering each question, participants completed a questionnaire to assess their perception of the engine's effect on the decision-making process in clinical practice. Of 300 possible pairs of answers (1 answer before and 1 after the initial search), 254 (85%) were produced by 14 residents. Of these, 132 (52%) and 122 (48%) pairs of answers concerned questions that had been assigned an initial search with InfoClinique and the Trip database, respectively. Both engines produced an important and similar absolute increase in the proportion of correct answers after searching (26% to 62% for InfoClinique, for an increase of 36%; 24% to 63% for the Trip database, for an increase of 39%; P = .68). For all 30 clinical questions, at least 1 resident produced the correct answer after searching with either search engine. The mean (SD) time of the initial search for each question was 23.5 (7.6) minutes with InfoClinique and 22.3 (7.8) minutes with the Trip database (P = .30). Participants' perceptions of each engine's effect on the decision-making process were very positive and similar for both search engines. Family medicine residents' ability to provide correct answers to clinical questions increased dramatically and similarly with the use of both InfoClinique and the Trip database. These tools have strong potential to increase the quality of medical care.

Helping Students Choose Tools To Search the Web.

ERIC Educational Resources Information Center

Cohen, Laura B.; Jacobson, Trudi E.

2000-01-01

Describes areas where faculty members can aid students in making intelligent use of the Web in their research. Differentiates between subject directories and search engines. Describes an engine's three components: spider, index, and search engine. Outlines two misconceptions: that Yahoo! is a search engine and that search engines contain all the…

The Brazilian Portuguese Lexicon: An Instrument for Psycholinguistic Research

PubMed Central

Estivalet, Gustavo L.; Meunier, Fanny

2015-01-01

In this article, we present the Brazilian Portuguese Lexicon, a new word-based corpus for psycholinguistic and computational linguistic research in Brazilian Portuguese. We describe the corpus development, the specific characteristics on the internet site and database for user access. We also perform distributional analyses of the corpus and comparisons to other current databases. Our main objective was to provide a large, reliable, and useful word-based corpus with a dynamic, easy-to-use, and intuitive interface with free internet access for word and word-criteria searches. We used the Núcleo Interinstitucional de Linguística Computacional’s corpus as the basic data source and developed the Brazilian Portuguese Lexicon by deriving and adding metalinguistic and psycholinguistic information about Brazilian Portuguese words. We obtained a final corpus with more than 30 million word tokens, 215 thousand word types and 25 categories of information about each word. This corpus was made available on the internet via a free-access site with two search engines: a simple search and a complex search. The simple engine basically searches for a list of words, while the complex engine accepts all types of criteria in the corpus categories. The output result presents all entries found in the corpus with the criteria specified in the input search and can be downloaded as a.csv file. We created a module in the results that delivers basic statistics about each search. The Brazilian Portuguese Lexicon also provides a pseudoword engine and specific tools for linguistic and statistical analysis. Therefore, the Brazilian Portuguese Lexicon is a convenient instrument for stimulus search, selection, control, and manipulation in psycholinguistic experiments, as also it is a powerful database for computational linguistics research and language modeling related to lexicon distribution, functioning, and behavior. PMID:26630138

The Brazilian Portuguese Lexicon: An Instrument for Psycholinguistic Research.

PubMed

Estivalet, Gustavo L; Meunier, Fanny

2015-01-01

In this article, we present the Brazilian Portuguese Lexicon, a new word-based corpus for psycholinguistic and computational linguistic research in Brazilian Portuguese. We describe the corpus development, the specific characteristics on the internet site and database for user access. We also perform distributional analyses of the corpus and comparisons to other current databases. Our main objective was to provide a large, reliable, and useful word-based corpus with a dynamic, easy-to-use, and intuitive interface with free internet access for word and word-criteria searches. We used the Núcleo Interinstitucional de Linguística Computacional's corpus as the basic data source and developed the Brazilian Portuguese Lexicon by deriving and adding metalinguistic and psycholinguistic information about Brazilian Portuguese words. We obtained a final corpus with more than 30 million word tokens, 215 thousand word types and 25 categories of information about each word. This corpus was made available on the internet via a free-access site with two search engines: a simple search and a complex search. The simple engine basically searches for a list of words, while the complex engine accepts all types of criteria in the corpus categories. The output result presents all entries found in the corpus with the criteria specified in the input search and can be downloaded as a.csv file. We created a module in the results that delivers basic statistics about each search. The Brazilian Portuguese Lexicon also provides a pseudoword engine and specific tools for linguistic and statistical analysis. Therefore, the Brazilian Portuguese Lexicon is a convenient instrument for stimulus search, selection, control, and manipulation in psycholinguistic experiments, as also it is a powerful database for computational linguistics research and language modeling related to lexicon distribution, functioning, and behavior.

Grooker, KartOO, Addict-o-Matic and More: Really Different Search Engines

ERIC Educational Resources Information Center

Descy, Don E.

2009-01-01

There are hundreds of unique search engines in the United States and thousands of unique search engines around the world. If people get into search engines designed just to search particular web sites, the number is in the hundreds of thousands. This article looks at: (1) clustering search engines, such as KartOO (www.kartoo.com) and Grokker…

Cochlear implantation: An assessment of quality and readability of web-based information aimed at patients.

PubMed

Seymour, Nicky; Lakhani, Raj; Hartley, Benjamin; Cochrane, Lesley; Jephson, Christopher

2015-01-01

Patients should have access to high-quality health information websites on which to base their decision-making. There are concerns regarding the accuracy and quality of some health websites. We aimed to objectively measure website quality related to cochlear implantation. Selected patient-information websites were scored, depending on how highly they ranked on search engines and if they were ranked on more than one of the search engines used. The top 40 websites from three major search engines were analysed. The quality of each website was scored using the DISCERN tool and the readability was scored using the Flesch-Kincaid reading ease and the Gunning-Fog index. The average Flesch-Kincaid score was 49.7, giving an average reading age of a 15-17 years old, and the average Gunning-fog score was 13.1, which equals that of an 18 years old. Internet-based information regarding cochlear implantation is of varied quality and is written above the expected reading level of an average person.

Adding a Visualization Feature to Web Search Engines: It’s Time

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, Pak C.

Since the first world wide web (WWW) search engine quietly entered our lives in 1994, the “information need” behind web searching has rapidly grown into a multi-billion dollar business that dominates the internet landscape, drives e-commerce traffic, propels global economy, and affects the lives of the whole human race. Today’s search engines are faster, smarter, and more powerful than those released just a few years ago. With the vast investment pouring into research and development by leading web technology providers and the intense emotion behind corporate slogans such as “win the web” or “take back the web,” I can’t helpmore » but ask why are we still using the very same “text-only” interface that was used 13 years ago to browse our search engine results pages (SERPs)? Why has the SERP interface technology lagged so far behind in the web evolution when the corresponding search technology has advanced so rapidly? In this article I explore some current SERP interface issues, suggest a simple but practical visual-based interface design approach, and argue why a visual approach can be a strong candidate for tomorrow’s SERP interface.« less

Making Temporal Search More Central in Spatial Data Infrastructures

NASA Astrophysics Data System (ADS)

Corti, P.; Lewis, B.

2017-10-01

A temporally enabled Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users, and tools intended to provide an efficient and flexible way to use spatial information which includes the historical dimension. One of the key software components of an SDI is the catalogue service which is needed to discover, query, and manage the metadata. A search engine is a software system capable of supporting fast and reliable search, which may use any means necessary to get users to the resources they need quickly and efficiently. These techniques may include features such as full text search, natural language processing, weighted results, temporal search based on enrichment, visualization of patterns in distributions of results in time and space using temporal and spatial faceting, and many others. In this paper we will focus on the temporal aspects of search which include temporal enrichment using a time miner - a software engine able to search for date components within a larger block of text, the storage of time ranges in the search engine, handling historical dates, and the use of temporal histograms in the user interface to display the temporal distribution of search results.

Evaluating a federated medical search engine: tailoring the methodology and reporting the evaluation outcomes.

PubMed

Saparova, D; Belden, J; Williams, J; Richardson, B; Schuster, K

2014-01-01

Federated medical search engines are health information systems that provide a single access point to different types of information. Their efficiency as clinical decision support tools has been demonstrated through numerous evaluations. Despite their rigor, very few of these studies report holistic evaluations of medical search engines and even fewer base their evaluations on existing evaluation frameworks. To evaluate a federated medical search engine, MedSocket, for its potential net benefits in an established clinical setting. This study applied the Human, Organization, and Technology (HOT-fit) evaluation framework in order to evaluate MedSocket. The hierarchical structure of the HOT-factors allowed for identification of a combination of efficiency metrics. Human fit was evaluated through user satisfaction and patterns of system use; technology fit was evaluated through the measurements of time-on-task and the accuracy of the found answers; and organization fit was evaluated from the perspective of system fit to the existing organizational structure. Evaluations produced mixed results and suggested several opportunities for system improvement. On average, participants were satisfied with MedSocket searches and confident in the accuracy of retrieved answers. However, MedSocket did not meet participants' expectations in terms of download speed, access to information, and relevance of the search results. These mixed results made it necessary to conclude that in the case of MedSocket, technology fit had a significant influence on the human and organization fit. Hence, improving technological capabilities of the system is critical before its net benefits can become noticeable. The HOT-fit evaluation framework was instrumental in tailoring the methodology for conducting a comprehensive evaluation of the search engine. Such multidimensional evaluation of the search engine resulted in recommendations for system improvement.

Evaluating a Federated Medical Search Engine

PubMed Central

Belden, J.; Williams, J.; Richardson, B.; Schuster, K.

2014-01-01

Summary Background Federated medical search engines are health information systems that provide a single access point to different types of information. Their efficiency as clinical decision support tools has been demonstrated through numerous evaluations. Despite their rigor, very few of these studies report holistic evaluations of medical search engines and even fewer base their evaluations on existing evaluation frameworks. Objectives To evaluate a federated medical search engine, MedSocket, for its potential net benefits in an established clinical setting. Methods This study applied the Human, Organization, and Technology (HOT-fit) evaluation framework in order to evaluate MedSocket. The hierarchical structure of the HOT-factors allowed for identification of a combination of efficiency metrics. Human fit was evaluated through user satisfaction and patterns of system use; technology fit was evaluated through the measurements of time-on-task and the accuracy of the found answers; and organization fit was evaluated from the perspective of system fit to the existing organizational structure. Results Evaluations produced mixed results and suggested several opportunities for system improvement. On average, participants were satisfied with MedSocket searches and confident in the accuracy of retrieved answers. However, MedSocket did not meet participants’ expectations in terms of download speed, access to information, and relevance of the search results. These mixed results made it necessary to conclude that in the case of MedSocket, technology fit had a significant influence on the human and organization fit. Hence, improving technological capabilities of the system is critical before its net benefits can become noticeable. Conclusions The HOT-fit evaluation framework was instrumental in tailoring the methodology for conducting a comprehensive evaluation of the search engine. Such multidimensional evaluation of the search engine resulted in recommendations for system improvement. PMID:25298813

[Advanced online search techniques and dedicated search engines for physicians].

PubMed

Nahum, Yoav

2008-02-01

In recent years search engines have become an essential tool in the work of physicians. This article will review advanced search techniques from the world of information specialists, as well as some advanced search engine operators that may help physicians improve their online search capabilities, and maximize the yield of their searches. This article also reviews popular dedicated scientific and biomedical literature search engines.

Image search engine with selective filtering and feature-element-based classification

NASA Astrophysics Data System (ADS)

Li, Qing; Zhang, Yujin; Dai, Shengyang

2001-12-01

With the growth of Internet and storage capability in recent years, image has become a widespread information format in World Wide Web. However, it has become increasingly harder to search for images of interest, and effective image search engine for the WWW needs to be developed. We propose in this paper a selective filtering process and a novel approach for image classification based on feature element in the image search engine we developed for the WWW. First a selective filtering process is embedded in a general web crawler to filter out the meaningless images with GIF format. Two parameters that can be obtained easily are used in the filtering process. Our classification approach first extract feature elements from images instead of feature vectors. Compared with feature vectors, feature elements can better capture visual meanings of the image according to subjective perception of human beings. Different from traditional image classification method, our classification approach based on feature element doesn't calculate the distance between two vectors in the feature space, while trying to find associations between feature element and class attribute of the image. Experiments are presented to show the efficiency of the proposed approach.

Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China.

PubMed

Du, Zhicheng; Xu, Lin; Zhang, Wangjian; Zhang, Dingmei; Yu, Shicheng; Hao, Yuantao

2017-10-06

Hand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD. Ecological study. Information on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011-2014. Analyses were conducted at aggregate level and no confidential information was involved. A seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI. A high correlation between HFMD incidence and BDI ( r =0.794, p<0.001) or temperature ( r =0.657, p<0.001) was observed using both time series plot and correlation matrix. A linear effect of BDI (without lag) and non-linear effect of temperature (1 week lag) on HFMD incidence were found in a distributed lag non-linear model. Compared with the model based on surveillance data only, the ARIMAX model including BDI reached the best goodness-of-fit with an Akaike information criterion (AIC) value of -345.332, whereas the model including both BDI and temperature had the most accurate prediction in terms of the mean absolute percentage error (MAPE) of 101.745%. An ARIMAX model incorporating search engine query data significantly improved the prediction of HFMD. Further studies are warranted to examine whether including search engine query data also improves the prediction of other infectious diseases in other settings. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China

PubMed Central

Du, Zhicheng; Xu, Lin; Zhang, Wangjian; Zhang, Dingmei; Yu, Shicheng; Hao, Yuantao

2017-01-01

Objectives Hand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD. Design Ecological study. Setting and participants Information on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011–2014. Analyses were conducted at aggregate level and no confidential information was involved. Outcome measures A seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI. Results A high correlation between HFMD incidence and BDI (r=0.794, p<0.001) or temperature (r=0.657, p<0.001) was observed using both time series plot and correlation matrix. A linear effect of BDI (without lag) and non-linear effect of temperature (1 week lag) on HFMD incidence were found in a distributed lag non-linear model. Compared with the model based on surveillance data only, the ARIMAX model including BDI reached the best goodness-of-fit with an Akaike information criterion (AIC) value of −345.332, whereas the model including both BDI and temperature had the most accurate prediction in terms of the mean absolute percentage error (MAPE) of 101.745%. Conclusions An ARIMAX model incorporating search engine query data significantly improved the prediction of HFMD. Further studies are warranted to examine whether including search engine query data also improves the prediction of other infectious diseases in other settings. PMID:28988169

Search Engines: Gateway to a New ``Panopticon''?

NASA Astrophysics Data System (ADS)

Kosta, Eleni; Kalloniatis, Christos; Mitrou, Lilian; Kavakli, Evangelia

Nowadays, Internet users are depending on various search engines in order to be able to find requested information on the Web. Although most users feel that they are and remain anonymous when they place their search queries, reality proves otherwise. The increasing importance of search engines for the location of the desired information on the Internet usually leads to considerable inroads into the privacy of users. The scope of this paper is to study the main privacy issues with regard to search engines, such as the anonymisation of search logs and their retention period, and to examine the applicability of the European data protection legislation to non-EU search engine providers. Ixquick, a privacy-friendly meta search engine will be presented as an alternative to privacy intrusive existing practices of search engines.

LoyalTracker: Visualizing Loyalty Dynamics in Search Engines.

PubMed

Shi, Conglei; Wu, Yingcai; Liu, Shixia; Zhou, Hong; Qu, Huamin

2014-12-01

The huge amount of user log data collected by search engine providers creates new opportunities to understand user loyalty and defection behavior at an unprecedented scale. However, this also poses a great challenge to analyze the behavior and glean insights into the complex, large data. In this paper, we introduce LoyalTracker, a visual analytics system to track user loyalty and switching behavior towards multiple search engines from the vast amount of user log data. We propose a new interactive visualization technique (flow view) based on a flow metaphor, which conveys a proper visual summary of the dynamics of user loyalty of thousands of users over time. Two other visualization techniques, a density map and a word cloud, are integrated to enable analysts to gain further insights into the patterns identified by the flow view. Case studies and the interview with domain experts are conducted to demonstrate the usefulness of our technique in understanding user loyalty and switching behavior in search engines.

Comparison of PubMed and Google Scholar literature searches.

PubMed

Anders, Michael E; Evans, Dennis P

2010-05-01

Literature searches are essential to evidence-based respiratory care. To conduct literature searches, respiratory therapists rely on search engines to retrieve information, but there is a dearth of literature on the comparative efficiencies of search engines for researching clinical questions in respiratory care. To compare PubMed and Google Scholar search results for clinical topics in respiratory care to that of a benchmark. We performed literature searches with PubMed and Google Scholar, on 3 clinical topics. In PubMed we used the Clinical Queries search filter. In Google Scholar we used the search filters in the Advanced Scholar Search option. We used the reference list of a related Cochrane Collaboration evidence-based systematic review as the benchmark for each of the search results. We calculated recall (sensitivity) and precision (positive predictive value) with 2 x 2 contingency tables. We compared the results with the chi-square test of independence and Fisher's exact test. PubMed and Google Scholar had similar recall for both overall search results (71% vs 69%) and full-text results (43% vs 51%). PubMed had better precision than Google Scholar for both overall search results (13% vs 0.07%, P < .001) and full-text results (8% vs 0.05%, P < .001). Our results suggest that PubMed searches with the Clinical Queries filter are more precise than with the Advanced Scholar Search in Google Scholar for respiratory care topics. PubMed appears to be more practical to conduct efficient, valid searches for informing evidence-based patient-care protocols, for guiding the care of individual patients, and for educational purposes.

Automatic sorting of toxicological information into the IUCLID (International Uniform Chemical Information Database) endpoint-categories making use of the semantic search engine Go3R.

PubMed

Sauer, Ursula G; Wächter, Thomas; Hareng, Lars; Wareing, Britta; Langsch, Angelika; Zschunke, Matthias; Alvers, Michael R; Landsiedel, Robert

2014-06-01

The knowledge-based search engine Go3R, www.Go3R.org, has been developed to assist scientists from industry and regulatory authorities in collecting comprehensive toxicological information with a special focus on identifying available alternatives to animal testing. The semantic search paradigm of Go3R makes use of expert knowledge on 3Rs methods and regulatory toxicology, laid down in the ontology, a network of concepts, terms, and synonyms, to recognize the contents of documents. Search results are automatically sorted into a dynamic table of contents presented alongside the list of documents retrieved. This table of contents allows the user to quickly filter the set of documents by topics of interest. Documents containing hazard information are automatically assigned to a user interface following the endpoint-specific IUCLID5 categorization scheme required, e.g. for REACH registration dossiers. For this purpose, complex endpoint-specific search queries were compiled and integrated into the search engine (based upon a gold standard of 310 references that had been assigned manually to the different endpoint categories). Go3R sorts 87% of the references concordantly into the respective IUCLID5 categories. Currently, Go3R searches in the 22 million documents available in the PubMed and TOXNET databases. However, it can be customized to search in other databases including in-house databanks. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comparing the diversity of information by word-of-mouth vs. web spread

NASA Astrophysics Data System (ADS)

Sela, Alon; Shekhtman, Louis; Havlin, Shlomo; Ben-Gal, Irad

2016-06-01

Many studies have explored spreading and diffusion through complex networks. The following study examines a specific case of spreading of opinions in modern society through two spreading schemes —defined as being either through “word of mouth” (WOM), or through online search engines (WEB). We apply both modelling and real experimental results and compare the opinions people adopt through an exposure to their friend's opinions, as opposed to the opinions they adopt when using a search engine based on the PageRank algorithm. A simulated study shows that when members in a population adopt decisions through the use of the WEB scheme, the population ends up with a few dominant views, while other views are barely expressed. In contrast, when members adopt decisions based on the WOM scheme, there is a far more diverse distribution of opinions in that population. The simulative results are further supported by an online experiment which finds that people searching information through a search engine end up with far more homogenous opinions as compared to those asking their friends.

Spiders and Worms and Crawlers, Oh My: Searching on the World Wide Web.

ERIC Educational Resources Information Center

Eagan, Ann; Bender, Laura

Searching on the world wide web can be confusing. A myriad of search engines exist, often with little or no documentation, and many of these search engines work differently from the standard search engines people are accustomed to using. Intended for librarians, this paper defines search engines, directories, spiders, and robots, and covers basics…

Dynamics of a macroscopic model characterizing mutualism of search engines and web sites

NASA Astrophysics Data System (ADS)

Wang, Yuanshi; Wu, Hong

2006-05-01

We present a model to describe the mutualism relationship between search engines and web sites. In the model, search engines and web sites benefit from each other while the search engines are derived products of the web sites and cannot survive independently. Our goal is to show strategies for the search engines to survive in the internet market. From mathematical analysis of the model, we show that mutualism does not always result in survival. We show various conditions under which the search engines would tend to extinction, persist or grow explosively. Then by the conditions, we deduce a series of strategies for the search engines to survive in the internet market. We present conditions under which the initial number of consumers of the search engines has little contribution to their persistence, which is in agreement with the results in previous works. Furthermore, we show novel conditions under which the initial value plays an important role in the persistence of the search engines and deduce new strategies. We also give suggestions for the web sites to cooperate with the search engines in order to form a win-win situation.

Discovery in a World of Mashups

NASA Astrophysics Data System (ADS)

King, T. A.; Ritschel, B.; Hourcle, J. A.; Moon, I. S.

2014-12-01

When the first digital information was stored electronically, discovery of what existed was through file names and the organization of the file system. With the advent of networks, digital information was shared on a wider scale, but discovery remained based on file and folder names. With a growing number of information sources, named based discovery quickly became ineffective. The keyword based search engine was one of the first types of a mashup in the world of Web 1.0. Embedded links from one document to another with prescribed relationships between files and the world of Web 2.0 was formed. Search engines like Google used the links to improve search results and a worldwide mashup was formed. While a vast improvement, the need for semantic (meaning rich) discovery was clear, especially for the discovery of scientific data. In response, every science discipline defined schemas to describe their type of data. Some core schemas where shared, but most schemas are custom tailored even though they share many common concepts. As with the networking of information sources, science increasingly relies on data from multiple disciplines. So there is a need to bring together multiple sources of semantically rich information. We explore how harvesting, conceptual mapping, facet based search engines, search term promotion, and style sheets can be combined to create the next generation of mashups in the emerging world of Web 3.0. We use NASA's Planetary Data System and NASA's Heliophysics Data Environment to illustrate how to create a multi-discipline mash-up.

An Exploratory Survey of Student Perspectives Regarding Search Engines

ERIC Educational Resources Information Center

Alshare, Khaled; Miller, Don; Wenger, James

2005-01-01

This study explored college students' perceptions regarding their use of search engines. The main objective was to determine how frequently students used various search engines, whether advanced search features were used, and how many search engines were used. Various factors that might influence student responses were examined. Results showed…

The Use of Web Search Engines in Information Science Research.

ERIC Educational Resources Information Center

Bar-Ilan, Judit

2004-01-01

Reviews the literature on the use of Web search engines in information science research, including: ways users interact with Web search engines; social aspects of searching; structure and dynamic nature of the Web; link analysis; other bibliometric applications; characterizing information on the Web; search engine evaluation and improvement; and…

Using JournalMap to link spatial information with ecological site descriptions

USDA-ARS?s Scientific Manuscript database

JournalMap is a scientific literature search engine that empowers you to find relevant research based on location and biophysical variables as well as traditional keyword searches. All publications are geotagged based on reported location information and plotted on a world map showing where the rese...

NASA Indexing Benchmarks: Evaluating Text Search Engines

NASA Technical Reports Server (NTRS)

Esler, Sandra L.; Nelson, Michael L.

1997-01-01

The current proliferation of on-line information resources underscores the requirement for the ability to index collections of information and search and retrieve them in a convenient manner. This study develops criteria for analytically comparing the index and search engines and presents results for a number of freely available search engines. A product of this research is a toolkit capable of automatically indexing, searching, and extracting performance statistics from each of the focused search engines. This toolkit is highly configurable and has the ability to run these benchmark tests against other engines as well. Results demonstrate that the tested search engines can be grouped into two levels. Level one engines are efficient on small to medium sized data collections, but show weaknesses when used for collections 100MB or larger. Level two search engines are recommended for data collections up to and beyond 100MB.

Autonomous entropy-based intelligent experimental design

NASA Astrophysics Data System (ADS)

Malakar, Nabin Kumar

2011-07-01

The aim of this thesis is to explore the application of probability and information theory in experimental design, and to do so in a way that combines what we know about inference and inquiry in a comprehensive and consistent manner. Present day scientific frontiers involve data collection at an ever-increasing rate. This requires that we find a way to collect the most relevant data in an automated fashion. By following the logic of the scientific method, we couple an inference engine with an inquiry engine to automate the iterative process of scientific learning. The inference engine involves Bayesian machine learning techniques to estimate model parameters based upon both prior information and previously collected data, while the inquiry engine implements data-driven exploration. By choosing an experiment whose distribution of expected results has the maximum entropy, the inquiry engine selects the experiment that maximizes the expected information gain. The coupled inference and inquiry engines constitute an autonomous learning method for scientific exploration. We apply it to a robotic arm to demonstrate the efficacy of the method. Optimizing inquiry involves searching for an experiment that promises, on average, to be maximally informative. If the set of potential experiments is described by many parameters, the search involves a high-dimensional entropy space. In such cases, a brute force search method will be slow and computationally expensive. We develop an entropy-based search algorithm, called nested entropy sampling, to select the most informative experiment. This helps to reduce the number of computations necessary to find the optimal experiment. We also extended the method of maximizing entropy, and developed a method of maximizing joint entropy so that it could be used as a principle of collaboration between two robots. This is a major achievement of this thesis, as it allows the information-based collaboration between two robotic units towards a same goal in an automated fashion.

Analysis of Web Spam for Non-English Content: Toward More Effective Language-Based Classifiers

PubMed Central

Alsaleh, Mansour; Alarifi, Abdulrahman

2016-01-01

Web spammers aim to obtain higher ranks for their web pages by including spam contents that deceive search engines in order to include their pages in search results even when they are not related to the search terms. Search engines continue to develop new web spam detection mechanisms, but spammers also aim to improve their tools to evade detection. In this study, we first explore the effect of the page language on spam detection features and we demonstrate how the best set of detection features varies according to the page language. We also study the performance of Google Penguin, a newly developed anti-web spamming technique for their search engine. Using spam pages in Arabic as a case study, we show that unlike similar English pages, Google anti-spamming techniques are ineffective against a high proportion of Arabic spam pages. We then explore multiple detection features for spam pages to identify an appropriate set of features that yields a high detection accuracy compared with the integrated Google Penguin technique. In order to build and evaluate our classifier, as well as to help researchers to conduct consistent measurement studies, we collected and manually labeled a corpus of Arabic web pages, including both benign and spam pages. Furthermore, we developed a browser plug-in that utilizes our classifier to warn users about spam pages after clicking on a URL and by filtering out search engine results. Using Google Penguin as a benchmark, we provide an illustrative example to show that language-based web spam classifiers are more effective for capturing spam contents. PMID:27855179

Analysis of Web Spam for Non-English Content: Toward More Effective Language-Based Classifiers.

PubMed

Alsaleh, Mansour; Alarifi, Abdulrahman

2016-01-01

Web spammers aim to obtain higher ranks for their web pages by including spam contents that deceive search engines in order to include their pages in search results even when they are not related to the search terms. Search engines continue to develop new web spam detection mechanisms, but spammers also aim to improve their tools to evade detection. In this study, we first explore the effect of the page language on spam detection features and we demonstrate how the best set of detection features varies according to the page language. We also study the performance of Google Penguin, a newly developed anti-web spamming technique for their search engine. Using spam pages in Arabic as a case study, we show that unlike similar English pages, Google anti-spamming techniques are ineffective against a high proportion of Arabic spam pages. We then explore multiple detection features for spam pages to identify an appropriate set of features that yields a high detection accuracy compared with the integrated Google Penguin technique. In order to build and evaluate our classifier, as well as to help researchers to conduct consistent measurement studies, we collected and manually labeled a corpus of Arabic web pages, including both benign and spam pages. Furthermore, we developed a browser plug-in that utilizes our classifier to warn users about spam pages after clicking on a URL and by filtering out search engine results. Using Google Penguin as a benchmark, we provide an illustrative example to show that language-based web spam classifiers are more effective for capturing spam contents.

Studies on behaviour of information to extract the meaning behind the behaviour

NASA Astrophysics Data System (ADS)

Nasution, M. K. M.; Syah, R.; Elveny, M.

2017-01-01

Web as social media can be used as a reference for determining social behaviour. However, the information extraction involves a search engine is not easy to give that picture. There are several properties of the search engine to be formally disclosed to provide assurance that the information is feasible. Although quite a lot of research that has revealed the interest of the Web as social media, but a few of them that have revealed behaviour of information related to social behaviour. In this case, it needs the formal steps to present possibilities related properties. There are 12 properties that are interconnected as behaviour of information and then it reveals several meanings based on the simulation results of any search engine.

Searching for a New Way to Reach Patrons: A Search Engine Optimization Pilot Project at Binghamton University Libraries

ERIC Educational Resources Information Center

Rushton, Erin E.; Kelehan, Martha Daisy; Strong, Marcy A.

2008-01-01

Search engine use is one of the most popular online activities. According to a recent OCLC report, nearly all students start their electronic research using a search engine instead of the library Web site. Instead of viewing search engines as competition, however, librarians at Binghamton University Libraries decided to employ search engine…

Teen smoking cessation help via the Internet: a survey of search engines.

PubMed

Edwards, Christine C; Elliott, Sean P; Conway, Terry L; Woodruff, Susan I

2003-07-01

The objective of this study was to assess Web sites related to teen smoking cessation on the Internet. Seven Internet search engines were searched using the keywords teen quit smoking. The top 20 hits from each search engine were reviewed and categorized. The keywords teen quit smoking produced between 35 and 400,000 hits depending on the search engine. Of 140 potential hits, 62% were active, unique sites; 85% were listed by only one search engine; and 40% focused on cessation. Findings suggest that legitimate on-line smoking cessation help for teens is constrained by search engine choice and the amount of time teens spend looking through potential sites. Resource listings should be updated regularly. Smoking cessation Web sites need to be picked up on multiple search engine searches. Further evaluation of smoking cessation Web sites need to be conducted to identify the most effective help for teens.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework

PubMed Central

2012-01-01

Background For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. Results We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. Conclusion The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources. PMID:23216909

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework.

PubMed

Lewis, Steven; Csordas, Attila; Killcoyne, Sarah; Hermjakob, Henning; Hoopmann, Michael R; Moritz, Robert L; Deutsch, Eric W; Boyle, John

2012-12-05

For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources.

[Development of domain specific search engines].

PubMed

Takai, T; Tokunaga, M; Maeda, K; Kaminuma, T

2000-01-01

As cyber space exploding in a pace that nobody has ever imagined, it becomes very important to search cyber space efficiently and effectively. One solution to this problem is search engines. Already a lot of commercial search engines have been put on the market. However these search engines respond with such cumbersome results that domain specific experts can not tolerate. Using a dedicate hardware and a commercial software called OpenText, we have tried to develop several domain specific search engines. These engines are for our institute's Web contents, drugs, chemical safety, endocrine disruptors, and emergent response for chemical hazard. These engines have been on our Web site for testing.

A Literature Review of Indexing and Searching Techniques Implementation in Educational Search Engines

ERIC Educational Resources Information Center

El Guemmat, Kamal; Ouahabi, Sara

2018-01-01

The objective of this article is to analyze the searching and indexing techniques of educational search engines' implementation while treating future challenges. Educational search engines could greatly help in the effectiveness of e-learning if used correctly. However, these engines have several gaps which influence the performance of e-learning…

Drexel at TREC 2014 Federated Web Search Track

DTIC Science & Technology

2014-11-01

of its input RS results. 1. INTRODUCTION Federated Web Search is the task of searching multiple search engines simultaneously and combining their...or distributed properly[5]. The goal of RS is then, for a given query, to select only the most promising search engines from all those available. Most...result pages of 149 search engines . 4000 queries are used in building the sample set. As a part of the Vertical Selection task, search engines are

Quality of Web-based information on obsessive compulsive disorder.

PubMed

Klila, Hedi; Chatton, Anne; Zermatten, Ariane; Khan, Riaz; Preisig, Martin; Khazaal, Yasser

2013-01-01

The Internet is increasingly used as a source of information for mental health issues. The burden of obsessive compulsive disorder (OCD) may lead persons with diagnosed or undiagnosed OCD, and their relatives, to search for good quality information on the Web. This study aimed to evaluate the quality of Web-based information on English-language sites dealing with OCD and to compare the quality of websites found through a general and a medically specialized search engine. Keywords related to OCD were entered into Google and OmniMedicalSearch. Websites were assessed on the basis of accountability, interactivity, readability, and content quality. The "Health on the Net" (HON) quality label and the Brief DISCERN scale score were used as possible content quality indicators. Of the 235 links identified, 53 websites were analyzed. The content quality of the OCD websites examined was relatively good. The use of a specialized search engine did not offer an advantage in finding websites with better content quality. A score ≥16 on the Brief DISCERN scale is associated with better content quality. This study shows the acceptability of the content quality of OCD websites. There is no advantage in searching for information with a specialized search engine rather than a general one. The Internet offers a number of high quality OCD websites. It remains critical, however, to have a provider-patient talk about the information found on the Web.

Multi-source and ontology-based retrieval engine for maize mutant phenotypes

PubMed Central

Green, Jason M.; Harnsomburana, Jaturon; Schaeffer, Mary L.; Lawrence, Carolyn J.; Shyu, Chi-Ren

2011-01-01

Model Organism Databases, including the various plant genome databases, collect and enable access to massive amounts of heterogeneous information, including sequence data, gene product information, images of mutant phenotypes, etc, as well as textual descriptions of many of these entities. While a variety of basic browsing and search capabilities are available to allow researchers to query and peruse the names and attributes of phenotypic data, next-generation search mechanisms that allow querying and ranking of text descriptions are much less common. In addition, the plant community needs an innovative way to leverage the existing links in these databases to search groups of text descriptions simultaneously. Furthermore, though much time and effort have been afforded to the development of plant-related ontologies, the knowledge embedded in these ontologies remains largely unused in available plant search mechanisms. Addressing these issues, we have developed a unique search engine for mutant phenotypes from MaizeGDB. This advanced search mechanism integrates various text description sources in MaizeGDB to aid a user in retrieving desired mutant phenotype information. Currently, descriptions of mutant phenotypes, loci and gene products are utilized collectively for each search, though expansion of the search mechanism to include other sources is straightforward. The retrieval engine, to our knowledge, is the first engine to exploit the content and structure of available domain ontologies, currently the Plant and Gene Ontologies, to expand and enrich retrieval results in major plant genomic databases. Database URL: http:www.PhenomicsWorld.org/QBTA.php PMID:21558151

Current Searching Methodology and Retrieval Issues: An Assessment

DTIC Science & Technology

2008-03-01

searching that are used by search engines are discussed. They are: full text searching, i.e., the searching of unstructured data, and metadata searching...also found among search engines ; however, it is the popularity of full text searching that has changed the road map to information access. The...other hand, information seekers’ willingness, or lack of, to learn the multiple search engines ’ capabilities may diminish their search results

eTACTS: a method for dynamically filtering clinical trial search results.

PubMed

Miotto, Riccardo; Jiang, Silis; Weng, Chunhua

2013-12-01

Information overload is a significant problem facing online clinical trial searchers. We present eTACTS, a novel interactive retrieval framework using common eligibility tags to dynamically filter clinical trial search results. eTACTS mines frequent eligibility tags from free-text clinical trial eligibility criteria and uses these tags for trial indexing. After an initial search, eTACTS presents to the user a tag cloud representing the current results. When the user selects a tag, eTACTS retains only those trials containing that tag in their eligibility criteria and generates a new cloud based on tag frequency and co-occurrences in the remaining trials. The user can then select a new tag or unselect a previous tag. The process iterates until a manageable number of trials is returned. We evaluated eTACTS in terms of filtering efficiency, diversity of the search results, and user eligibility to the filtered trials using both qualitative and quantitative methods. eTACTS (1) rapidly reduced search results from over a thousand trials to ten; (2) highlighted trials that are generally not top-ranked by conventional search engines; and (3) retrieved a greater number of suitable trials than existing search engines. eTACTS enables intuitive clinical trial searches by indexing eligibility criteria with effective tags. User evaluation was limited to one case study and a small group of evaluators due to the long duration of the experiment. Although a larger-scale evaluation could be conducted, this feasibility study demonstrated significant advantages of eTACTS over existing clinical trial search engines. A dynamic eligibility tag cloud can potentially enhance state-of-the-art clinical trial search engines by allowing intuitive and efficient filtering of the search result space. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

eTACTS: A Method for Dynamically Filtering Clinical Trial Search Results

PubMed Central

Miotto, Riccardo; Jiang, Silis; Weng, Chunhua

2013-01-01

Objective Information overload is a significant problem facing online clinical trial searchers. We present eTACTS, a novel interactive retrieval framework using common eligibility tags to dynamically filter clinical trial search results. Materials and Methods eTACTS mines frequent eligibility tags from free-text clinical trial eligibility criteria and uses these tags for trial indexing. After an initial search, eTACTS presents to the user a tag cloud representing the current results. When the user selects a tag, eTACTS retains only those trials containing that tag in their eligibility criteria and generates a new cloud based on tag frequency and co-occurrences in the remaining trials. The user can then select a new tag or unselect a previous tag. The process iterates until a manageable number of trials is returned. We evaluated eTACTS in terms of filtering efficiency, diversity of the search results, and user eligibility to the filtered trials using both qualitative and quantitative methods. Results eTACTS (1) rapidly reduced search results from over a thousand trials to ten; (2) highlighted trials that are generally not top-ranked by conventional search engines; and (3) retrieved a greater number of suitable trials than existing search engines. Discussion eTACTS enables intuitive clinical trial searches by indexing eligibility criteria with effective tags. User evaluation was limited to one case study and a small group of evaluators due to the long duration of the experiment. Although a larger-scale evaluation could be conducted, this feasibility study demonstrated significant advantages of eTACTS over existing clinical trial search engines. Conclusion A dynamic eligibility tag cloud can potentially enhance state-of-the-art clinical trial search engines by allowing intuitive and efficient filtering of the search result space. PMID:23916863

Fixing Dataset Search

NASA Technical Reports Server (NTRS)

Lynnes, Chris

2014-01-01

Three current search engines are queried for ozone data at the GES DISC. The results range from sub-optimal to counter-intuitive. We propose a method to fix dataset search by implementing a robust relevancy ranking scheme. The relevancy ranking scheme is based on several heuristics culled from more than 20 years of helping users select datasets.

EARS: An Online Bibliographic Search and Retrieval System Based on Ordered Explosion.

ERIC Educational Resources Information Center

Ramesh, R.; Drury, Colin G.

1987-01-01

Provides overview of Ergonomics Abstracts Retrieval System (EARS), an online bibliographic search and retrieval system in the area of human factors engineering. Other online systems are described, the design of EARS based on inverted file organization is explained, and system expansions including a thesaurus are discussed. (Author/LRW)

Are Parents Getting it Right? A Survey of Parents' Internet Use for Children's Health Care Information.

PubMed

Pehora, Carolyne; Gajaria, Nisha; Stoute, Melyssa; Fracassa, Sonia; Serebale-O'Sullivan, Refilwe; Matava, Clyde T

2015-06-22

The use of the Internet to search for medical and health-related information is increasing and associated with concerns around quality and safety. We investigated the current use and perceptions on reliable websites for children's health information by parents. Following institutional ethics approval, we conducted a survey of parents/guardians of children presenting for day surgery. A 20-item survey instrument developed and tested by the investigators was administered. Ninety-eight percent of respondents reported that they used the Internet to search for information about their child's health. Many respondents reported beginning their search at public search engines (80%); less than 20% reported starting their search at university/hospital-based websites. Common conditions such as colds/flu, skin conditions and fever were the most frequently searched, and unique conditions directly affecting the child were second. Despite low usage levels of university/hospital-based websites for health information, the majority of respondents (74%) regarded these as providing safe, accurate, and reliable information. In contrast, only 24% of respondents regarded public search engines as providing safe and reliable information. Fifty percent of respondents reported that they cross-checked information found on the internet with a family physician. An unprecedented majority of parents and guardians are using the Internet for their child's health information. Of concern is that parents and guardians are currently not using reliable and safe sources of information. Health care providers should begin to focus on improving access to safe, accurate, and reliable information through various modalities including education, designing for multiplatform, and better search engine optimization.

Discovery of gigantic molecular nanostructures using a flow reaction array as a search engine.

PubMed

Zang, Hong-Ying; de la Oliva, Andreu Ruiz; Miras, Haralampos N; Long, De-Liang; McBurney, Roy T; Cronin, Leroy

2014-04-28

The discovery of gigantic molecular nanostructures like coordination and polyoxometalate clusters is extremely time-consuming since a vast combinatorial space needs to be searched, and even a systematic and exhaustive exploration of the available synthetic parameters relies on a great deal of serendipity. Here we present a synthetic methodology that combines a flow reaction array and algorithmic control to give a chemical 'real-space' search engine leading to the discovery and isolation of a range of new molecular nanoclusters based on [Mo(2)O(2)S(2)](2+)-based building blocks with either fourfold (C4) or fivefold (C5) symmetry templates and linkers. This engine leads us to isolate six new nanoscale cluster compounds: 1, {Mo(10)(C5)}; 2, {Mo(14)(C4)4(C5)2}; 3, {Mo(60)(C4)10}; 4, {Mo(48)(C4)6}; 5, {Mo(34)(C4)4}; 6, {Mo(18)(C4)9}; in only 200 automated experiments from a parameter space spanning ~5 million possible combinations.

Foraging patterns in online searches.

PubMed

Wang, Xiangwen; Pleimling, Michel

2017-03-01

Nowadays online searches are undeniably the most common form of information gathering, as witnessed by billions of clicks generated each day on search engines. In this work we describe online searches as foraging processes that take place on the semi-infinite line. Using a variety of quantities like probability distributions and complementary cumulative distribution functions of step length and waiting time as well as mean square displacements and entropies, we analyze three different click-through logs that contain the detailed information of millions of queries submitted to search engines. Notable differences between the different logs reveal an increased efficiency of the search engines. In the language of foraging, the newer logs indicate that online searches overwhelmingly yield local searches (i.e., on one page of links provided by the search engines), whereas for the older logs the foraging processes are a combination of local searches and relocation phases that are power law distributed. Our investigation of click logs of search engines therefore highlights the presence of intermittent search processes (where phases of local explorations are separated by power law distributed relocation jumps) in online searches. It follows that good search engines enable the users to find the information they are looking for through a local exploration of a single page with search results, whereas for poor search engine users are often forced to do a broader exploration of different pages.

Foraging patterns in online searches

NASA Astrophysics Data System (ADS)

Wang, Xiangwen; Pleimling, Michel

2017-03-01

Nowadays online searches are undeniably the most common form of information gathering, as witnessed by billions of clicks generated each day on search engines. In this work we describe online searches as foraging processes that take place on the semi-infinite line. Using a variety of quantities like probability distributions and complementary cumulative distribution functions of step length and waiting time as well as mean square displacements and entropies, we analyze three different click-through logs that contain the detailed information of millions of queries submitted to search engines. Notable differences between the different logs reveal an increased efficiency of the search engines. In the language of foraging, the newer logs indicate that online searches overwhelmingly yield local searches (i.e., on one page of links provided by the search engines), whereas for the older logs the foraging processes are a combination of local searches and relocation phases that are power law distributed. Our investigation of click logs of search engines therefore highlights the presence of intermittent search processes (where phases of local explorations are separated by power law distributed relocation jumps) in online searches. It follows that good search engines enable the users to find the information they are looking for through a local exploration of a single page with search results, whereas for poor search engine users are often forced to do a broader exploration of different pages.

Regional Value Analysis at Threat Evaluation

DTIC Science & Technology

2014-06-01

targets based on information entropy and fuzzy optimization theory. in Industrial Engineering and Engineering Management (IEEM), 2011 IEEE...Assignment by Virtual Permutation and Tabu Search Heuristics. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 2010

A fuzzy-match search engine for physician directories.

PubMed

Rastegar-Mojarad, Majid; Kadolph, Christopher; Ye, Zhan; Wall, Daniel; Murali, Narayana; Lin, Simon

2014-11-04

A search engine to find physicians' information is a basic but crucial function of a health care provider's website. Inefficient search engines, which return no results or incorrect results, can lead to patient frustration and potential customer loss. A search engine that can handle misspellings and spelling variations of names is needed, as the United States (US) has culturally, racially, and ethnically diverse names. The Marshfield Clinic website provides a search engine for users to search for physicians' names. The current search engine provides an auto-completion function, but it requires an exact match. We observed that 26% of all searches yielded no results. The goal was to design a fuzzy-match algorithm to aid users in finding physicians easier and faster. Instead of an exact match search, we used a fuzzy algorithm to find similar matches for searched terms. In the algorithm, we solved three types of search engine failures: "Typographic", "Phonetic spelling variation", and "Nickname". To solve these mismatches, we used a customized Levenshtein distance calculation that incorporated Soundex coding and a lookup table of nicknames derived from US census data. Using the "Challenge Data Set of Marshfield Physician Names," we evaluated the accuracy of fuzzy-match engine-top ten (90%) and compared it with exact match (0%), Soundex (24%), Levenshtein distance (59%), and fuzzy-match engine-top one (71%). We designed, created a reference implementation, and evaluated a fuzzy-match search engine for physician directories. The open-source code is available at the codeplex website and a reference implementation is available for demonstration at the datamarsh website.

Locality in Search Engine Queries and Its Implications for Caching

DTIC Science & Technology

2001-05-01

in the question of whether caching might be effective for search engines as well. They study two real search engine traces by examining query...locality and its implications for caching. The two search engines studied are Vivisimo and Excite. Their trace analysis results show that queries have

Variability of patient spine education by Internet search engine.

PubMed

Ghobrial, George M; Mehdi, Angud; Maltenfort, Mitchell; Sharan, Ashwini D; Harrop, James S

2014-03-01

Patients are increasingly reliant upon the Internet as a primary source of medical information. The educational experience varies by search engine, search term, and changes daily. There are no tools for critical evaluation of spinal surgery websites. To highlight the variability between common search engines for the same search terms. To detect bias, by prevalence of specific kinds of websites for certain spinal disorders. Demonstrate a simple scoring system of spinal disorder website for patient use, to maximize the quality of information exposed to the patient. Ten common search terms were used to query three of the most common search engines. The top fifty results of each query were tabulated. A negative binomial regression was performed to highlight the variation across each search engine. Google was more likely than Bing and Yahoo search engines to return hospital ads (P=0.002) and more likely to return scholarly sites of peer-reviewed lite (P=0.003). Educational web sites, surgical group sites, and online web communities had a significantly higher likelihood of returning on any search, regardless of search engine, or search string (P=0.007). Likewise, professional websites, including hospital run, industry sponsored, legal, and peer-reviewed web pages were less likely to be found on a search overall, regardless of engine and search string (P=0.078). The Internet is a rapidly growing body of medical information which can serve as a useful tool for patient education. High quality information is readily available, provided that the patient uses a consistent, focused metric for evaluating online spine surgery information, as there is a clear variability in the way search engines present information to the patient. Published by Elsevier B.V.

Evaluation of Proteomic Search Engines for the Analysis of Histone Modifications

PubMed Central

2015-01-01

Identification of histone post-translational modifications (PTMs) is challenging for proteomics search engines. Including many histone PTMs in one search increases the number of candidate peptides dramatically, leading to low search speed and fewer identified spectra. To evaluate database search engines on identifying histone PTMs, we present a method in which one kind of modification is searched each time, for example, unmodified, individually modified, and multimodified, each search result is filtered with false discovery rate less than 1%, and the identifications of multiple search engines are combined to obtain confident results. We apply this method for eight search engines on histone data sets. We find that two search engines, pFind and Mascot, identify most of the confident results at a reasonable speed, so we recommend using them to identify histone modifications. During the evaluation, we also find some important aspects for the analysis of histone modifications. Our evaluation of different search engines on identifying histone modifications will hopefully help those who are hoping to enter the histone proteomics field. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD001118. PMID:25167464

Evaluation of proteomic search engines for the analysis of histone modifications.

PubMed

Yuan, Zuo-Fei; Lin, Shu; Molden, Rosalynn C; Garcia, Benjamin A

2014-10-03

Identification of histone post-translational modifications (PTMs) is challenging for proteomics search engines. Including many histone PTMs in one search increases the number of candidate peptides dramatically, leading to low search speed and fewer identified spectra. To evaluate database search engines on identifying histone PTMs, we present a method in which one kind of modification is searched each time, for example, unmodified, individually modified, and multimodified, each search result is filtered with false discovery rate less than 1%, and the identifications of multiple search engines are combined to obtain confident results. We apply this method for eight search engines on histone data sets. We find that two search engines, pFind and Mascot, identify most of the confident results at a reasonable speed, so we recommend using them to identify histone modifications. During the evaluation, we also find some important aspects for the analysis of histone modifications. Our evaluation of different search engines on identifying histone modifications will hopefully help those who are hoping to enter the histone proteomics field. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD001118.

Surveillance Tools Emerging From Search Engines and Social Media Data for Determining Eye Disease Patterns.

PubMed

Deiner, Michael S; Lietman, Thomas M; McLeod, Stephen D; Chodosh, James; Porco, Travis C

2016-09-01

Internet-based search engine and social media data may provide a novel complementary source for better understanding the epidemiologic factors of infectious eye diseases, which could better inform eye health care and disease prevention. To assess whether data from internet-based social media and search engines are associated with objective clinic-based diagnoses of conjunctivitis. Data from encounters of 4143 patients diagnosed with conjunctivitis from June 3, 2012, to April 26, 2014, at the University of California San Francisco (UCSF) Medical Center, were analyzed using Spearman rank correlation of each weekly observation to compare demographics and seasonality of nonallergic conjunctivitis with allergic conjunctivitis. Data for patient encounters with diagnoses for glaucoma and influenza were also obtained for the same period and compared with conjunctivitis. Temporal patterns of Twitter and Google web search data, geolocated to the United States and associated with these clinical diagnoses, were compared with the clinical encounters. The a priori hypothesis was that weekly internet-based searches and social media posts about conjunctivitis may reflect the true weekly clinical occurrence of conjunctivitis. Weekly total clinical diagnoses at UCSF of nonallergic conjunctivitis, allergic conjunctivitis, glaucoma, and influenza were compared using Spearman rank correlation with equivalent weekly data on Tweets related to disease or disease-related keyword searches obtained from Google Trends. Seasonality of clinical diagnoses of nonallergic conjunctivitis among the 4143 patients (2364 females [57.1%] and 1776 males [42.9%]) with 5816 conjunctivitis encounters at UCSF correlated strongly with results of Google searches in the United States for the term pink eye (ρ, 0.68 [95% CI, 0.52 to 0.78]; P < .001) and correlated moderately with Twitter results about pink eye (ρ, 0.38 [95% CI, 0.16 to 0.56]; P < .001) and with clinical diagnosis of influenza (ρ, 0.33 [95% CI, 0.12 to 0.49]; P < .001), but did not significantly correlate with seasonality of clinical diagnoses of allergic conjunctivitis diagnosis at UCSF (ρ, 0.21 [95% CI, -0.02 to 0.42]; P = .06) or with results of Google searches in the United States for the term eye allergy (ρ, 0.13 [95% CI, -0.06 to 0.32]; P = .19). Seasonality of clinical diagnoses of allergic conjunctivitis at UCSF correlated strongly with results of Google searches in the United States for the term eye allergy (ρ, 0.44 [95% CI, 0.24 to 0.60]; P < .001) and eye drops (ρ, 0.47 [95% CI, 0.27 to 0.62]; P < .001). Internet-based search engine and social media data may reflect the occurrence of clinically diagnosed conjunctivitis, suggesting that these data sources can be leveraged to better understand the epidemiologic factors of conjunctivitis.

A Study of HTML Title Tag Creation Behavior of Academic Web Sites

ERIC Educational Resources Information Center

Noruzi, Alireza

2007-01-01

The HTML title tag information should identify and describe exactly what a Web page contains. This paper analyzes the "Title element" and raises a significant question: "Why is the title tag important?" Search engines base search results and page rankings on certain criteria. Among the most important criteria is the presence of the search keywords…

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

The Effectiveness of Web Search Engines to Index New Sites from Different Countries

ERIC Educational Resources Information Center

Pirkola, Ari

2009-01-01

Introduction: Investigates how effectively Web search engines index new sites from different countries. The primary interest is whether new sites are indexed equally or whether search engines are biased towards certain countries. If major search engines show biased coverage it can be considered a significant economic and political problem because…

Taming the Information Jungle with WWW Search Engines.

ERIC Educational Resources Information Center

Repman, Judi; And Others

1997-01-01

Because searching the Web with different engines often produces different results, the best strategy is to learn how each engine works. Discusses comparing search engines; qualities to consider (ease of use, relevance of hits, and speed); and six of the most popular search tools (Yahoo, Magellan. InfoSeek, Alta Vista, Lycos, and Excite). Lists…

MIRASS: medical informatics research activity support system using information mashup network.

PubMed

Kiah, M L M; Zaidan, B B; Zaidan, A A; Nabi, Mohamed; Ibraheem, Rabiu

2014-04-01

The advancement of information technology has facilitated the automation and feasibility of online information sharing. The second generation of the World Wide Web (Web 2.0) enables the collaboration and sharing of online information through Web-serving applications. Data mashup, which is considered a Web 2.0 platform, plays an important role in information and communication technology applications. However, few ideas have been transformed into education and research domains, particularly in medical informatics. The creation of a friendly environment for medical informatics research requires the removal of certain obstacles in terms of search time, resource credibility, and search result accuracy. This paper considers three glitches that researchers encounter in medical informatics research; these glitches include the quality of papers obtained from scientific search engines (particularly, Web of Science and Science Direct), the quality of articles from the indices of these search engines, and the customizability and flexibility of these search engines. A customizable search engine for trusted resources of medical informatics was developed and implemented through data mashup. Results show that the proposed search engine improves the usability of scientific search engines for medical informatics. Pipe search engine was found to be more efficient than other engines.

Comparing Web search engine performance in searching consumer health information: evaluation and recommendations.

PubMed Central

Wu, G; Li, J

1999-01-01

Identifying and accessing reliable, relevant consumer health information rapidly on the Internet may challenge the health sciences librarian and layperson alike. In this study, seven search engines are compared using representative consumer health topics for their content relevancy, system features, and attributes. The paper discusses evaluation criteria; systematically compares relevant results; analyzes performance in terms of the strengths and weaknesses of the search engines; and illustrates effective search engine selection, search formulation, and strategies. PMID:10550031

Islamic Extremists Love the Internet

DTIC Science & Technology

2009-04-03

down on the West. Terrorists’ Use of Search Engines In order to find a particular blog, extremists use search engines such as Bloglines...BlogScope, and Technorati to search blog contents. Technorati, which is among the most popular blog search engines , provides current information on...of mid- January 2009 is tracking over 31.78 million blogs with 579.86 million posts.49 Other ways the terrorists use Web search engines are to

Combinatorial Fusion Analysis for Meta Search Information Retrieval

NASA Astrophysics Data System (ADS)

Hsu, D. Frank; Taksa, Isak

Leading commercial search engines are built as single event systems. In response to a particular search query, the search engine returns a single list of ranked search results. To find more relevant results the user must frequently try several other search engines. A meta search engine was developed to enhance the process of multi-engine querying. The meta search engine queries several engines at the same time and fuses individual engine results into a single search results list. The fusion of multiple search results has been shown (mostly experimentally) to be highly effective. However, the question of why and how the fusion should be done still remains largely unanswered. In this chapter, we utilize the combinatorial fusion analysis proposed by Hsu et al. to analyze combination and fusion of multiple sources of information. A rank/score function is used in the design and analysis of our framework. The framework provides a better understanding of the fusion phenomenon in information retrieval. For example, to improve the performance of the combined multiple scoring systems, it is necessary that each of the individual scoring systems has relatively high performance and the individual scoring systems are diverse. Additionally, we illustrate various applications of the framework using two examples from the information retrieval domain.

Is Internet search better than structured instruction for web-based health education?

PubMed

Finkelstein, Joseph; Bedra, McKenzie

2013-01-01

Internet provides access to vast amounts of comprehensive information regarding any health-related subject. Patients increasingly use this information for health education using a search engine to identify education materials. An alternative approach of health education via Internet is based on utilizing a verified web site which provides structured interactive education guided by adult learning theories. Comparison of these two approaches in older patients was not performed systematically. The aim of this study was to compare the efficacy of a web-based computer-assisted education (CO-ED) system versus searching the Internet for learning about hypertension. Sixty hypertensive older adults (age 45+) were randomized into control or intervention groups. The control patients spent 30 to 40 minutes searching the Internet using a search engine for information about hypertension. The intervention patients spent 30 to 40 minutes using the CO-ED system, which provided computer-assisted instruction about major hypertension topics. Analysis of pre- and post- knowledge scores indicated a significant improvement among CO-ED users (14.6%) as opposed to Internet users (2%). Additionally, patients using the CO-ED program rated their learning experience more positively than those using the Internet.

Search Engines on the World Wide Web.

ERIC Educational Resources Information Center

Walster, Dian

1997-01-01

Discusses search engines and provides methods for determining what resources are searched, the quality of the information, and the algorithms used that will improve the use of search engines on the World Wide Web, online public access catalogs, and electronic encyclopedias. Lists strategies for conducting searches and for learning about the latest…

The Mercury System: Embedding Computation into Disk Drives

DTIC Science & Technology

2004-08-20

enabling technologies to build extremely fast data search engines . We do this by moving the search closer to the data, and performing it in hardware...engine searches in parallel across a disk or disk surface 2. System Parallelism: Searching is off-loaded to search engines and main processor can

[Biomedical information on the internet using search engines. A one-year trial].

PubMed

Corrao, Salvatore; Leone, Francesco; Arnone, Sabrina

2004-01-01

The internet is a communication medium and content distributor that provide information in the general sense but it could be of great utility regarding as the search and retrieval of biomedical information. Search engines represent a great deal to rapidly find information on the net. However, we do not know whether general search engines and meta-search ones are reliable in order to find useful and validated biomedical information. The aim of our study was to verify the reproducibility of a search by key-words (pediatric or evidence) using 9 international search engines and 1 meta-search engine at the baseline and after a one year period. We analysed the first 20 citations as output of each searching. We evaluated the formal quality of Web-sites and their domain extensions. Moreover, we compared the output of each search at the start of this study and after a one year period and we considered as a criterion of reliability the number of Web-sites cited again. We found some interesting results that are reported throughout the text. Our findings point out an extreme dynamicity of the information on the Web and, for this reason, we advice a great caution when someone want to use search and meta-search engines as a tool for searching and retrieve reliable biomedical information. On the other hand, some search and meta-search engines could be very useful as a first step searching for defining better a search and, moreover, for finding institutional Web-sites too. This paper allows to know a more conscious approach to the internet biomedical information universe.

Development of a Google-based search engine for data mining radiology reports.

PubMed

Erinjeri, Joseph P; Picus, Daniel; Prior, Fred W; Rubin, David A; Koppel, Paul

2009-08-01

The aim of this study is to develop a secure, Google-based data-mining tool for radiology reports using free and open source technologies and to explore its use within an academic radiology department. A Health Insurance Portability and Accountability Act (HIPAA)-compliant data repository, search engine and user interface were created to facilitate treatment, operations, and reviews preparatory to research. The Institutional Review Board waived review of the project, and informed consent was not required. Comprising 7.9 GB of disk space, 2.9 million text reports were downloaded from our radiology information system to a fileserver. Extensible markup language (XML) representations of the reports were indexed using Google Desktop Enterprise search engine software. A hypertext markup language (HTML) form allowed users to submit queries to Google Desktop, and Google's XML response was interpreted by a practical extraction and report language (PERL) script, presenting ranked results in a web browser window. The query, reason for search, results, and documents visited were logged to maintain HIPAA compliance. Indexing averaged approximately 25,000 reports per hour. Keyword search of a common term like "pneumothorax" yielded the first ten most relevant results of 705,550 total results in 1.36 s. Keyword search of a rare term like "hemangioendothelioma" yielded the first ten most relevant results of 167 total results in 0.23 s; retrieval of all 167 results took 0.26 s. Data mining tools for radiology reports will improve the productivity of academic radiologists in clinical, educational, research, and administrative tasks. By leveraging existing knowledge of Google's interface, radiologists can quickly perform useful searches.

Alternative Fuels Data Center: Vehicle Search

Science.gov Websites

ZeroTruck Search Engines and Hybrid Systems For medium- and heavy-duty vehicles: Engine & Power Sources Hydraulic hybrid Hybrid - CNG Hybrid - Diesel Electric Hybrid - LNG Hybrid Search x Pick Engine Fuel Natural Gas Propane Electric Plug-in Hybrid Electric Hydraulic hybrid Hybrid Search x Pick Engine Fuel

Getting to the top of Google: search engine optimization.

PubMed

Maley, Catherine; Baum, Neil

2010-01-01

Search engine optimization is the process of making your Web site appear at or near the top of popular search engines such as Google, Yahoo, and MSN. This is not done by luck or knowing someone working for the search engines but by understanding the process of how search engines select Web sites for placement on top or on the first page. This article will review the process and provide methods and techniques to use to have your site rated at the top or very near the top.

Combining results of multiple search engines in proteomics.

PubMed

Shteynberg, David; Nesvizhskii, Alexey I; Moritz, Robert L; Deutsch, Eric W

2013-09-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

Combining Results of Multiple Search Engines in Proteomics*

PubMed Central

Shteynberg, David; Nesvizhskii, Alexey I.; Moritz, Robert L.; Deutsch, Eric W.

2013-01-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques. PMID:23720762

EasyKSORD: A Platform of Keyword Search Over Relational Databases

NASA Astrophysics Data System (ADS)

Peng, Zhaohui; Li, Jing; Wang, Shan

Keyword Search Over Relational Databases (KSORD) enables casual users to use keyword queries (a set of keywords) to search relational databases just like searching the Web, without any knowledge of the database schema or any need of writing SQL queries. Based on our previous work, we design and implement a novel KSORD platform named EasyKSORD for users and system administrators to use and manage different KSORD systems in a novel and simple manner. EasyKSORD supports advanced queries, efficient data-graph-based search engines, multiform result presentations, and system logging and analysis. Through EasyKSORD, users can search relational databases easily and read search results conveniently, and system administrators can easily monitor and analyze the operations of KSORD and manage KSORD systems much better.

Location-based Web Search

NASA Astrophysics Data System (ADS)

Ahlers, Dirk; Boll, Susanne

In recent years, the relation of Web information to a physical location has gained much attention. However, Web content today often carries only an implicit relation to a location. In this chapter, we present a novel location-based search engine that automatically derives spatial context from unstructured Web resources and allows for location-based search: our focused crawler applies heuristics to crawl and analyze Web pages that have a high probability of carrying a spatial relation to a certain region or place; the location extractor identifies the actual location information from the pages; our indexer assigns a geo-context to the pages and makes them available for a later spatial Web search. We illustrate the usage of our spatial Web search for location-based applications that provide information not only right-in-time but also right-on-the-spot.

The Extreme Searcher's Guide to Web Search Engines: A Handbook for the Serious Searcher. 2nd Edition.

ERIC Educational Resources Information Center

Hock, Randolph

This book aims to facilitate more effective and efficient use of World Wide Web search engines by helping the reader: know the basic structure of the major search engines; become acquainted with those attributes (features, benefits, options, content, etc.) that search engines have in common and where they differ; know the main strengths and…

Research on Agriculture Domain Meta-Search Engine System

NASA Astrophysics Data System (ADS)

Xie, Nengfu; Wang, Wensheng

The rapid growth of agriculture web information brings a fact that search engine can not return a satisfied result for users’ queries. In this paper, we propose an agriculture domain search engine system, called ADSE, that can obtains results by an advance interface to several searches and aggregates them. We also discuss two key technologies: agriculture information determination and engine.

The impact of search engine selection and sorting criteria on vaccination beliefs and attitudes: two experiments manipulating Google output.

PubMed

Allam, Ahmed; Schulz, Peter Johannes; Nakamoto, Kent

2014-04-02

During the past 2 decades, the Internet has evolved to become a necessity in our daily lives. The selection and sorting algorithms of search engines exert tremendous influence over the global spread of information and other communication processes. This study is concerned with demonstrating the influence of selection and sorting/ranking criteria operating in search engines on users' knowledge, beliefs, and attitudes of websites about vaccination. In particular, it is to compare the effects of search engines that deliver websites emphasizing on the pro side of vaccination with those focusing on the con side and with normal Google as a control group. We conducted 2 online experiments using manipulated search engines. A pilot study was to verify the existence of dangerous health literacy in connection with searching and using health information on the Internet by exploring the effect of 2 manipulated search engines that yielded either pro or con vaccination sites only, with a group receiving normal Google as control. A pre-post test design was used; participants were American marketing students enrolled in a study-abroad program in Lugano, Switzerland. The second experiment manipulated the search engine by applying different ratios of con versus pro vaccination webpages displayed in the search results. Participants were recruited from Amazon's Mechanical Turk platform where it was published as a human intelligence task (HIT). Both experiments showed knowledge highest in the group offered only pro vaccination sites (Z=-2.088, P=.03; Kruskal-Wallis H test [H₅]=11.30, P=.04). They acknowledged the importance/benefits (Z=-2.326, P=.02; H5=11.34, P=.04) and effectiveness (Z=-2.230, P=.03) of vaccination more, whereas groups offered antivaccination sites only showed increased concern about effects (Z=-2.582, P=.01; H₅=16.88, P=.005) and harmful health outcomes (Z=-2.200, P=.02) of vaccination. Normal Google users perceived information quality to be positive despite a small effect on knowledge and a negative effect on their beliefs and attitudes toward vaccination and willingness to recommend the information (χ²₅=14.1, P=.01). More exposure to antivaccination websites lowered participants' knowledge (J=4783.5, z=-2.142, P=.03) increased their fear of side effects (J=6496, z=2.724, P=.006), and lowered their acknowledgment of benefits (J=4805, z=-2.067, P=.03). The selection and sorting/ranking criteria of search engines play a vital role in online health information seeking. Search engines delivering websites containing credible and evidence-based medical information impact positively Internet users seeking health information. Whereas sites retrieved by biased search engines create some opinion change in users. These effects are apparently independent of users' site credibility and evaluation judgments. Users are affected beneficially or detrimentally but are unaware, suggesting they are not consciously perceptive of indicators that steer them toward the credible sources or away from the dangerous ones. In this sense, the online health information seeker is flying blind.

The Impact of Search Engine Selection and Sorting Criteria on Vaccination Beliefs and Attitudes: Two Experiments Manipulating Google Output

PubMed Central

Schulz, Peter Johannes; Nakamoto, Kent

2014-01-01

Background During the past 2 decades, the Internet has evolved to become a necessity in our daily lives. The selection and sorting algorithms of search engines exert tremendous influence over the global spread of information and other communication processes. Objective This study is concerned with demonstrating the influence of selection and sorting/ranking criteria operating in search engines on users’ knowledge, beliefs, and attitudes of websites about vaccination. In particular, it is to compare the effects of search engines that deliver websites emphasizing on the pro side of vaccination with those focusing on the con side and with normal Google as a control group. Method We conducted 2 online experiments using manipulated search engines. A pilot study was to verify the existence of dangerous health literacy in connection with searching and using health information on the Internet by exploring the effect of 2 manipulated search engines that yielded either pro or con vaccination sites only, with a group receiving normal Google as control. A pre-post test design was used; participants were American marketing students enrolled in a study-abroad program in Lugano, Switzerland. The second experiment manipulated the search engine by applying different ratios of con versus pro vaccination webpages displayed in the search results. Participants were recruited from Amazon’s Mechanical Turk platform where it was published as a human intelligence task (HIT). Results Both experiments showed knowledge highest in the group offered only pro vaccination sites (Z=–2.088, P=.03; Kruskal-Wallis H test [H5]=11.30, P=.04). They acknowledged the importance/benefits (Z=–2.326, P=.02; H5=11.34, P=.04) and effectiveness (Z=–2.230, P=.03) of vaccination more, whereas groups offered antivaccination sites only showed increased concern about effects (Z=–2.582, P=.01; H5=16.88, P=.005) and harmful health outcomes (Z=–2.200, P=.02) of vaccination. Normal Google users perceived information quality to be positive despite a small effect on knowledge and a negative effect on their beliefs and attitudes toward vaccination and willingness to recommend the information (χ2 5=14.1, P=.01). More exposure to antivaccination websites lowered participants’ knowledge (J=4783.5, z=−2.142, P=.03) increased their fear of side effects (J=6496, z=2.724, P=.006), and lowered their acknowledgment of benefits (J=4805, z=–2.067, P=.03). Conclusion The selection and sorting/ranking criteria of search engines play a vital role in online health information seeking. Search engines delivering websites containing credible and evidence-based medical information impact positively Internet users seeking health information. Whereas sites retrieved by biased search engines create some opinion change in users. These effects are apparently independent of users’ site credibility and evaluation judgments. Users are affected beneficially or detrimentally but are unaware, suggesting they are not consciously perceptive of indicators that steer them toward the credible sources or away from the dangerous ones. In this sense, the online health information seeker is flying blind. PMID:24694866

Using Internet search engines to estimate word frequency.

PubMed

Blair, Irene V; Urland, Geoffrey R; Ma, Jennifer E

2002-05-01

The present research investigated Internet search engines as a rapid, cost-effective alternative for estimating word frequencies. Frequency estimates for 382 words were obtained and compared across four methods: (1) Internet search engines, (2) the Kucera and Francis (1967) analysis of a traditional linguistic corpus, (3) the CELEX English linguistic database (Baayen, Piepenbrock, & Gulikers, 1995), and (4) participant ratings of familiarity. The results showed that Internet search engines produced frequency estimates that were highly consistent with those reported by Kucera and Francis and those calculated from CELEX, highly consistent across search engines, and very reliable over a 6-month period of time. Additional results suggested that Internet search engines are an excellent option when traditional word frequency analyses do not contain the necessary data (e.g., estimates for forenames and slang). In contrast, participants' familiarity judgments did not correspond well with the more objective estimates of word frequency. Researchers are advised to use search engines with large databases (e.g., AltaVista) to ensure the greatest representativeness of the frequency estimates.

CAMEL: concept annotated image libraries

NASA Astrophysics Data System (ADS)

Natsev, Apostol; Chadha, Atul; Soetarman, Basuki; Vitter, Jeffrey S.

2001-01-01

The problem of content-based image searching has received considerable attention in the last few years. Thousands of images are now available on the Internet, and many important applications require searching of images in domains such as E-commerce, medical imaging, weather prediction, satellite imagery, and so on. Yet, content-based image querying is still largely unestablished as a mainstream field, nor is it widely used by search engines. We believe that two of the major hurdles for this poor acceptance are poor retrieval quality and usability.

CAMEL: concept annotated image libraries

NASA Astrophysics Data System (ADS)

Natsev, Apostol; Chadha, Atul; Soetarman, Basuki; Vitter, Jeffrey S.

2000-12-01

The problem of content-based image searching has received considerable attention in the last few years. Thousands of images are now available on the Internet, and many important applications require searching of images in domains such as E-commerce, medical imaging, weather prediction, satellite imagery, and so on. Yet, content-based image querying is still largely unestablished as a mainstream field, nor is it widely used by search engines. We believe that two of the major hurdles for this poor acceptance are poor retrieval quality and usability.

ReSEARCH: A Requirements Search Engine: Progress Report 2

DTIC Science & Technology

2008-09-01

and provides a convenient user interface for the search process. Ideally, the web application would be based on Tomcat, a free Java Servlet and JSP...Implementation issues Lucene Java is an Open Source project, available under the Apache License, which provides an accessible API for the development of...from the Apache Lucene website (Lucene- java Wiki , 2008). A search application developed with Lucene consists of the same two major com- ponents

MSblender: A probabilistic approach for integrating peptide identifications from multiple database search engines.

PubMed

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I; Marcotte, Edward M

2011-07-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for every possible PSM and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for most proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses.

MSblender: a probabilistic approach for integrating peptide identifications from multiple database search engines

PubMed Central

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I.; Marcotte, Edward M.

2011-01-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for all possible PSMs and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for all detected proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses. PMID:21488652

Searching the Internet for information on prostate cancer screening: an assessment of quality.

PubMed

Ilic, Dragan; Risbridger, Gail; Green, Sally

2004-07-01

To identify how on-line information relating to prostate cancer screening (PCS) is best sourced, whether through general, medical, or meta-search engines, and to assess the quality of that information. Websites providing information about PCS were searched across 15 search engines representing three distinct types: general, medical, and meta-search engines. The quality of on-line information was assessed using the DISCERN quality assessment tool. Quality performance characteristics were analyzed by performing Mann-Whitney U tests. Search engine efficiency was measured by each search query as a percentage of the relevant websites included for analysis from the total returned and analyzed by performing Kruskal-Wallis analysis of variance. Of 6690 websites reviewed, 84 unique websites were identified as providing information relevant to PCS. General and meta-search engines were significantly more efficient at retrieving relevant information on PCS compared with medical search engines. The quality of information was variable, with most of a poor standard. Websites that provided referral links to other resources and a citation of evidence provided a significantly better quality of information. In contrast, websites offering a direct service were more likely to provide a significantly poorer quality of information. The current lack of a clear consensus on guidelines and recommendation in published data is also reflected by the variable quality of information found on-line. Specialized medical search engines were no more likely to retrieve relevant, high-quality information than general or meta-search engines.

Seeking health information online: does Wikipedia matter?

PubMed

Laurent, Michaël R; Vickers, Tim J

2009-01-01

OBJECTIVE To determine the significance of the English Wikipedia as a source of online health information. DESIGN The authors measured Wikipedia's ranking on general Internet search engines by entering keywords from MedlinePlus, NHS Direct Online, and the National Organization of Rare Diseases as queries into search engine optimization software. We assessed whether article quality influenced this ranking. The authors tested whether traffic to Wikipedia coincided with epidemiological trends and news of emerging health concerns, and how it compares to MedlinePlus. MEASUREMENTS Cumulative incidence and average position of Wikipedia compared to other Web sites among the first 20 results on general Internet search engines (Google, Google UK, Yahoo, and MSN, and page view statistics for selected Wikipedia articles and MedlinePlus pages. RESULTS Wikipedia ranked among the first ten results in 71-85% of search engines and keywords tested. Wikipedia surpassed MedlinePlus and NHS Direct Online (except for queries from the latter on Google UK), and ranked higher with quality articles. Wikipedia ranked highest for rare diseases, although its incidence in several categories decreased. Page views increased parallel to the occurrence of 20 seasonal disorders and news of three emerging health concerns. Wikipedia articles were viewed more often than MedlinePlus Topic (p = 0.001) but for MedlinePlus Encyclopedia pages, the trend was not significant (p = 0.07-0.10). CONCLUSIONS Based on its search engine ranking and page view statistics, the English Wikipedia is a prominent source of online health information compared to the other online health information providers studied.

Comparison of Four Search Engines and their efficacy With Emphasis on Literature Research in Addiction (Prevention and Treatment).

PubMed

Samadzadeh, Gholam Reza; Rigi, Tahereh; Ganjali, Ali Reza

2013-01-01

Surveying valuable and most recent information from internet, has become vital for researchers and scholars, because every day, thousands and perhaps millions of scientific works are brought out as digital resources which represented by internet and researchers can't ignore this great resource to find related documents for their literature search, which may not be found in any library. With regard to variety of documents presented on the internet, search engines are one of the most effective search tools for finding information. The aim of this study is to evaluate the three criteria, recall, preciseness and importance of the four search engines which are PubMed, Science Direct, Google Scholar and federated search of Iranian National Medical Digital Library in addiction (prevention and treatment) to select the most effective search engine for offering the best literature research. This research was a cross-sectional study by which four popular search engines in medical sciences were evaluated. To select keywords, medical subject heading (Mesh) was used. We entered given keywords in the search engines and after searching, 10 first entries were evaluated. Direct observation was used as a mean for data collection and they were analyzed by descriptive statistics (number, percent number and mean) and inferential statistics, One way analysis of variance (ANOVA) and post hoc Tukey in Spss. 15 statistical software. P Value < 0.05 was considered statistically significant. Results have shown that the search engines had different operations with regard to the evaluated criteria. Since P Value was 0.004 < 0.05 for preciseness and was 0.002 < 0.05 for importance, it shows significant difference among search engines. PubMed, Science Direct and Google Scholar were the best in recall, preciseness and importance respectively. As literature research is one of the most important stages of research, it's better for researchers, especially Substance-Related Disorders scholars to use different search engines with the best recall, preciseness and importance in that subject field to reach desirable results while searching and they don't depend on just one search engine.

Comparison of Four Search Engines and their efficacy With Emphasis on Literature Research in Addiction (Prevention and Treatment)

PubMed Central

Samadzadeh, Gholam Reza; Rigi, Tahereh; Ganjali, Ali Reza

2013-01-01

Background Surveying valuable and most recent information from internet, has become vital for researchers and scholars, because every day, thousands and perhaps millions of scientific works are brought out as digital resources which represented by internet and researchers can’t ignore this great resource to find related documents for their literature search, which may not be found in any library. With regard to variety of documents presented on the internet, search engines are one of the most effective search tools for finding information. Objectives The aim of this study is to evaluate the three criteria, recall, preciseness and importance of the four search engines which are PubMed, Science Direct, Google Scholar and federated search of Iranian National Medical Digital Library in addiction (prevention and treatment) to select the most effective search engine for offering the best literature research. Materials and Methods This research was a cross-sectional study by which four popular search engines in medical sciences were evaluated. To select keywords, medical subject heading (Mesh) was used. We entered given keywords in the search engines and after searching, 10 first entries were evaluated. Direct observation was used as a mean for data collection and they were analyzed by descriptive statistics (number, percent number and mean) and inferential statistics, One way analysis of variance (ANOVA) and post hoc Tukey in Spss. 15 statistical software. P Value < 0.05 was considered statistically significant. Results Results have shown that the search engines had different operations with regard to the evaluated criteria. Since P Value was 0.004 < 0.05 for preciseness and was 0.002 < 0.05 for importance, it shows significant difference among search engines. PubMed, Science Direct and Google Scholar were the best in recall, preciseness and importance respectively. Conclusions As literature research is one of the most important stages of research, it's better for researchers, especially Substance-Related Disorders scholars to use different search engines with the best recall, preciseness and importance in that subject field to reach desirable results while searching and they don’t depend on just one search engine. PMID:24971257

Search Engine Liability for Copyright Infringement

NASA Astrophysics Data System (ADS)

Fitzgerald, B.; O'Brien, D.; Fitzgerald, A.

The chapter provides a broad overview to the topic of search engine liability for copyright infringement. In doing so, the chapter examines some of the key copyright law principles and their application to search engines. The chapter also provides a discussion of some of the most important cases to be decided within the courts of the United States, Australia, China and Europe regarding the liability of search engines for copyright infringement. Finally, the chapter will conclude with some thoughts for reform, including how copyright law can be amended in order to accommodate and realise the great informative power which search engines have to offer society.

Defining and Exposing Privacy Issues with Social Media

DTIC Science & Technology

2012-06-11

Twitter, and Linked In[ I 0). VI. SEARCH ENGINES In addition to social networking sites, search engines pose new issues to privacy. As...networking, search engines , and storing personal information online in general have been accepted worldwide due to the benefits they provide. Social...networking provides even more communication in an information-demanding age, allowing users to interact across great distances. Search engines allow

Developing Information Storage and Retrieval Systems on the Internet: A Knowledge Management Approach

DTIC Science & Technology

2011-09-01

search engines to find information. Most commercial search engines (Google, Yahoo, Bing, etc.) provide their indexing and search services...at no cost. The DoD can achieve large gains at a small cost by making public documents available to search engines . This can be achieved through the...were organized on the website dodreports.com. The results of this research revealed improvement gains of 8-20% for finding reports through commercial search engines during the first six months of

Can people find patient decision aids on the Internet?

PubMed

Morris, Debra; Drake, Elizabeth; Saarimaki, Anton; Bennett, Carol; O'Connor, Annette

2008-12-01

To determine if people could find patient decision aids (PtDAs) on the Internet using the most popular general search engines. We chose five medical conditions for which English language PtDAs were available from at least three different developers. The search engines used were: Google (www.google.com), Yahoo! (www.yahoo.com), and MSN (www.msn.com). For each condition and search engine we ran six searches using a combination of search terms. We coded all non-sponsored Web pages that were linked from the first page of the search results. Most first page results linked to informational Web pages about the condition, only 16% linked to PtDAs. PtDAs were more readily found for the breast cancer surgery decision (our searches found seven of the nine developers). The searches using Yahoo and Google search engines were more likely to find PtDAs. The following combination of search terms: condition, treatment, decision (e.g. breast cancer surgery decision) was most successful across all search engines (29%). While some terms and search engines were more successful, few resulted in direct links to PtDAs. Finding PtDAs would be improved with use of standardized labelling, providing patients with specific Web site addresses or access to an independent PtDA clearinghouse.

Mirador: A Simple, Fast Search Interface for Remote Sensing Data

NASA Technical Reports Server (NTRS)

Lynnes, Christopher; Strub, Richard; Seiler, Edward; Joshi, Talak; MacHarrie, Peter

2008-01-01

A major challenge for remote sensing science researchers is searching and acquiring relevant data files for their research projects based on content, space and time constraints. Several structured query (SQ) and hierarchical navigation (HN) search interfaces have been develop ed to satisfy this requirement, yet the dominant search engines in th e general domain are based on free-text search. The Goddard Earth Sci ences Data and Information Services Center has developed a free-text search interface named Mirador that supports space-time queries, inc luding a gazetteer and geophysical event gazetteer. In order to compe nsate for a slightly reduced search precision relative to SQ and HN t echniques, Mirador uses several search optimizations to return result s quickly. The quick response enables a more iterative search strateg y than is available with many SQ and HN techniques.

Discovery of gigantic molecular nanostructures using a flow reaction array as a search engine

PubMed Central

Zang, Hong-Ying; de la Oliva, Andreu Ruiz; Miras, Haralampos N.; Long, De-Liang; McBurney, Roy T.; Cronin, Leroy

2014-01-01

The discovery of gigantic molecular nanostructures like coordination and polyoxometalate clusters is extremely time-consuming since a vast combinatorial space needs to be searched, and even a systematic and exhaustive exploration of the available synthetic parameters relies on a great deal of serendipity. Here we present a synthetic methodology that combines a flow reaction array and algorithmic control to give a chemical ‘real-space’ search engine leading to the discovery and isolation of a range of new molecular nanoclusters based on [Mo2O2S2]2+-based building blocks with either fourfold (C4) or fivefold (C5) symmetry templates and linkers. This engine leads us to isolate six new nanoscale cluster compounds: 1, {Mo10(C5)}; 2, {Mo14(C4)4(C5)2}; 3, {Mo60(C4)10}; 4, {Mo48(C4)6}; 5, {Mo34(C4)4}; 6, {Mo18(C4)9}; in only 200 automated experiments from a parameter space spanning ~5 million possible combinations. PMID:24770632

A novel knowledge-based system for interpreting complex engineering drawings: theory, representation, and implementation.

PubMed

Lu, Tong; Tai, Chiew-Lan; Yang, Huafei; Cai, Shijie

2009-08-01

We present a novel knowledge-based system to automatically convert real-life engineering drawings to content-oriented high-level descriptions. The proposed method essentially turns the complex interpretation process into two parts: knowledge representation and knowledge-based interpretation. We propose a new hierarchical descriptor-based knowledge representation method to organize the various types of engineering objects and their complex high-level relations. The descriptors are defined using an Extended Backus Naur Form (EBNF), facilitating modification and maintenance. When interpreting a set of related engineering drawings, the knowledge-based interpretation system first constructs an EBNF-tree from the knowledge representation file, then searches for potential engineering objects guided by a depth-first order of the nodes in the EBNF-tree. Experimental results and comparisons with other interpretation systems demonstrate that our knowledge-based system is accurate and robust for high-level interpretation of complex real-life engineering projects.

GEMINI: a computationally-efficient search engine for large gene expression datasets.

PubMed

DeFreitas, Timothy; Saddiki, Hachem; Flaherty, Patrick

2016-02-24

Low-cost DNA sequencing allows organizations to accumulate massive amounts of genomic data and use that data to answer a diverse range of research questions. Presently, users must search for relevant genomic data using a keyword, accession number of meta-data tag. However, in this search paradigm the form of the query - a text-based string - is mismatched with the form of the target - a genomic profile. To improve access to massive genomic data resources, we have developed a fast search engine, GEMINI, that uses a genomic profile as a query to search for similar genomic profiles. GEMINI implements a nearest-neighbor search algorithm using a vantage-point tree to store a database of n profiles and in certain circumstances achieves an [Formula: see text] expected query time in the limit. We tested GEMINI on breast and ovarian cancer gene expression data from The Cancer Genome Atlas project and show that it achieves a query time that scales as the logarithm of the number of records in practice on genomic data. In a database with 10(5) samples, GEMINI identifies the nearest neighbor in 0.05 sec compared to a brute force search time of 0.6 sec. GEMINI is a fast search engine that uses a query genomic profile to search for similar profiles in a very large genomic database. It enables users to identify similar profiles independent of sample label, data origin or other meta-data information.

Decision making in family medicine

PubMed Central

Labrecque, Michel; Ratté, Stéphane; Frémont, Pierre; Cauchon, Michel; Ouellet, Jérôme; Hogg, William; McGowan, Jessie; Gagnon, Marie-Pierre; Njoya, Merlin; Légaré, France

2013-01-01

Abstract Objective To compare the ability of users of 2 medical search engines, InfoClinique and the Trip database, to provide correct answers to clinical questions and to explore the perceived effects of the tools on the clinical decision-making process. Design Randomized trial. Setting Three family medicine units of the family medicine program of the Faculty of Medicine at Laval University in Quebec city, Que. Participants Fifteen second-year family medicine residents. Intervention Residents generated 30 structured questions about therapy or preventive treatment (2 questions per resident) based on clinical encounters. Using an Internet platform designed for the trial, each resident answered 20 of these questions (their own 2, plus 18 of the questions formulated by other residents, selected randomly) before and after searching for information with 1 of the 2 search engines. For each question, 5 residents were randomly assigned to begin their search with InfoClinique and 5 with the Trip database. Main outcome measures The ability of residents to provide correct answers to clinical questions using the search engines, as determined by third-party evaluation. After answering each question, participants completed a questionnaire to assess their perception of the engine’s effect on the decision-making process in clinical practice. Results Of 300 possible pairs of answers (1 answer before and 1 after the initial search), 254 (85%) were produced by 14 residents. Of these, 132 (52%) and 122 (48%) pairs of answers concerned questions that had been assigned an initial search with InfoClinique and the Trip database, respectively. Both engines produced an important and similar absolute increase in the proportion of correct answers after searching (26% to 62% for InfoClinique, for an increase of 36%; 24% to 63% for the Trip database, for an increase of 39%; P = .68). For all 30 clinical questions, at least 1 resident produced the correct answer after searching with either search engine. The mean (SD) time of the initial search for each question was 23.5 (7.6) minutes with InfoClinique and 22.3 (7.8) minutes with the Trip database (P = .30). Participants’ perceptions of each engine’s effect on the decision-making process were very positive and similar for both search engines. Conclusion Family medicine residents’ ability to provide correct answers to clinical questions increased dramatically and similarly with the use of both InfoClinique and the Trip database. These tools have strong potential to increase the quality of medical care. PMID:24130286

Surveillance Tools Emerging From Search Engines and Social Media Data for Determining Eye Disease Patterns

PubMed Central

Deiner, Michael S.; Lietman, Thomas M.; McLeod, Stephen D.; Chodosh, James; Porco, Travis C.

2016-01-01

IMPORTANCE Internet-based search engine and social media data may provide a novel complementary source for better understanding the epidemiologic factors of infectious eye diseases, which could better inform eye health care and disease prevention. OBJECTIVE To assess whether data from internet-based social media and search engines are associated with objective clinic-based diagnoses of conjunctivitis. DESIGN, SETTING, AND PARTICIPANTS Data from encounters of 4143 patients diagnosed with conjunctivitis from June 3, 2012, to April 26, 2014, at the University of California San Francisco (UCSF) Medical Center, were analyzed using Spearman rank correlation of each weekly observation to compare demographics and seasonality of nonallergic conjunctivitis with allergic conjunctivitis. Data for patient encounters with diagnoses for glaucoma and influenza were also obtained for the same period and compared with conjunctivitis. Temporal patterns of Twitter and Google web search data, geolocated to the United States and associated with these clinical diagnoses, were compared with the clinical encounters. The a priori hypothesis was that weekly internet-based searches and social media posts about conjunctivitis may reflect the true weekly clinical occurrence of conjunctivitis. MAIN OUTCOMES AND MEASURES Weekly total clinical diagnoses at UCSF of nonallergic conjunctivitis, allergic conjunctivitis, glaucoma, and influenza were compared using Spearman rank correlation with equivalent weekly data on Tweets related to disease or disease-related keyword searches obtained from Google Trends. RESULTS Seasonality of clinical diagnoses of nonallergic conjunctivitis among the 4143 patients (2364 females [57.1%] and 1776 males [42.9%]) with 5816 conjunctivitis encounters at UCSF correlated strongly with results of Google searches in the United States for the term pink eye (ρ, 0.68 [95%CI, 0.52 to 0.78]; P < .001) and correlated moderately with Twitter results about pink eye (ρ, 0.38 [95%CI, 0.16 to 0.56]; P < .001) and with clinical diagnosis of influenza (ρ, 0.33 [95%CI, 0.12 to 0.49]; P < .001), but did not significantly correlate with seasonality of clinical diagnoses of allergic conjunctivitis diagnosis at UCSF (ρ, 0.21 [95%CI, −0.02 to 0.42]; P = .06) or with results of Google searches in the United States for the term eye allergy (ρ, 0.13 [95%CI, −0.06 to 0.32]; P = .19). Seasonality of clinical diagnoses of allergic conjunctivitis at UCSF correlated strongly with results of Google searches in the United States for the term eye allergy (ρ, 0.44 [95%CI, 0.24 to 0.60]; P < .001) and eye drops (ρ, 0.47 [95%CI, 0.27 to 0.62]; P < .001). CONCLUSIONS AND RELEVANCE Internet-based search engine and social media data may reflect the occurrence of clinically diagnosed conjunctivitis, suggesting that these data sources can be leveraged to better understand the epidemiologic factors of conjunctivitis. PMID:27416554

Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM

NASA Astrophysics Data System (ADS)

Sheng, Hanlin; Zhang, Tianhong

2017-08-01

In view of the necessity of highly precise and reliable thrust estimator to achieve direct thrust control of aircraft engine, based on support vector regression (SVR), as well as least square support vector machine (LSSVM) and a new optimization algorithm - gravitational search algorithm (GSA), by performing integrated modelling and parameter optimization, a GSA-LSSVM-based thrust estimator design solution is proposed. The results show that compared to particle swarm optimization (PSO) algorithm, GSA can find unknown optimization parameter better and enables the model developed with better prediction and generalization ability. The model can better predict aircraft engine thrust and thus fulfills the need of direct thrust control of aircraft engine.

Problems of information support in scientific research

NASA Astrophysics Data System (ADS)

Shamaev, V. G.; Gorshkov, A. B.

2015-11-01

This paper reports on the creation of the open access Akustika portal (AKDATA.RU) designed to provide Russian-language easy-to-read and search information on acoustics and related topics. The absence of a Russian-language publication in foreign databases means that it is effectively lost for much of the scientific community. The portal has three interrelated sections: the Akustika information search system (ISS) (Acoustics), full-text archive of the Akusticheskii Zhurnal (Acoustic Journal), and 'Signal'naya informatsiya' ('Signaling information') on acoustics. The paper presents a description of the Akustika ISS, including its structure, content, interface, and information search capabilities for basic and applied research in diverse areas of science, engineering, biology, medicine, etc. The intended users of the portal are physicists, engineers, and engineering technologists interested in expanding their research activities and seeking to increase their knowledge base. Those studying current trends in the Russian-language contribution to international science may also find the portal useful.

Publications - Search Help | Alaska Division of Geological & Geophysical

Science.gov Websites

main content Publications Search Help General Hints The search engine will retrieve those publications publication's title is known, enter those words in the title input box. The search engine will look for all of .). Publication Year The search engine will retrieve all publication years by default. Select one publication year

Biogeography-based particle swarm optimization with fuzzy elitism and its applications to constrained engineering problems

NASA Astrophysics Data System (ADS)

Guo, Weian; Li, Wuzhao; Zhang, Qun; Wang, Lei; Wu, Qidi; Ren, Hongliang

2014-11-01

In evolutionary algorithms, elites are crucial to maintain good features in solutions. However, too many elites can make the evolutionary process stagnate and cannot enhance the performance. This article employs particle swarm optimization (PSO) and biogeography-based optimization (BBO) to propose a hybrid algorithm termed biogeography-based particle swarm optimization (BPSO) which could make a large number of elites effective in searching optima. In this algorithm, the whole population is split into several subgroups; BBO is employed to search within each subgroup and PSO for the global search. Since not all the population is used in PSO, this structure overcomes the premature convergence in the original PSO. Time complexity analysis shows that the novel algorithm does not increase the time consumption. Fourteen numerical benchmarks and four engineering problems with constraints are used to test the BPSO. To better deal with constraints, a fuzzy strategy for the number of elites is investigated. The simulation results validate the feasibility and effectiveness of the proposed algorithm.

Construction of nested maximin designs based on successive local enumeration and modified novel global harmony search algorithm

NASA Astrophysics Data System (ADS)

Yi, Jin; Li, Xinyu; Xiao, Mi; Xu, Junnan; Zhang, Lin

2017-01-01

Engineering design often involves different types of simulation, which results in expensive computational costs. Variable fidelity approximation-based design optimization approaches can realize effective simulation and efficiency optimization of the design space using approximation models with different levels of fidelity and have been widely used in different fields. As the foundations of variable fidelity approximation models, the selection of sample points of variable-fidelity approximation, called nested designs, is essential. In this article a novel nested maximin Latin hypercube design is constructed based on successive local enumeration and a modified novel global harmony search algorithm. In the proposed nested designs, successive local enumeration is employed to select sample points for a low-fidelity model, whereas the modified novel global harmony search algorithm is employed to select sample points for a high-fidelity model. A comparative study with multiple criteria and an engineering application are employed to verify the efficiency of the proposed nested designs approach.

Web information retrieval based on ontology

NASA Astrophysics Data System (ADS)

Zhang, Jian

2013-03-01

The purpose of the Information Retrieval (IR) is to find a set of documents that are relevant for a specific information need of a user. Traditional Information Retrieval model commonly used in commercial search engine is based on keyword indexing system and Boolean logic queries. One big drawback of traditional information retrieval is that they typically retrieve information without an explicitly defined domain of interest to the users so that a lot of no relevance information returns to users, which burden the user to pick up useful answer from these no relevance results. In order to tackle this issue, many semantic web information retrieval models have been proposed recently. The main advantage of Semantic Web is to enhance search mechanisms with the use of Ontology's mechanisms. In this paper, we present our approach to personalize web search engine based on ontology. In addition, key techniques are also discussed in our paper. Compared to previous research, our works concentrate on the semantic similarity and the whole process including query submission and information annotation.

Intelligent web image retrieval system

NASA Astrophysics Data System (ADS)

Hong, Sungyong; Lee, Chungwoo; Nah, Yunmook

2001-07-01

Recently, the web sites such as e-business sites and shopping mall sites deal with lots of image information. To find a specific image from these image sources, we usually use web search engines or image database engines which rely on keyword only retrievals or color based retrievals with limited search capabilities. This paper presents an intelligent web image retrieval system. We propose the system architecture, the texture and color based image classification and indexing techniques, and representation schemes of user usage patterns. The query can be given by providing keywords, by selecting one or more sample texture patterns, by assigning color values within positional color blocks, or by combining some or all of these factors. The system keeps track of user's preferences by generating user query logs and automatically add more search information to subsequent user queries. To show the usefulness of the proposed system, some experimental results showing recall and precision are also explained.

Creative Thinking of Practical Engineering Students During a Design Project

NASA Astrophysics Data System (ADS)

Waks, Shlomo; Merdler, Moti

2003-01-01

Creativity in engineering design had become an economic necessity and not merely the privilege of unique individuals. The search for new, innovative and effective ideas in engineering design stands in center of daily creative performance. This search requires sensitivity to gaps of knowledge and information, and the ability to evoke numerous, different and unique ideas about engineering problems. The source of such information or knowledge can be either extrinsic-such as provided by an instructor or expert or intrinsic, which might involve transformation from one field or context to another. Furthermore, interaction with an exterior source as well as developing an inherent drive, have an impact on the motivation to perform creatively. This article, which is based on a study conducted among Israeli practical engineering students, deals with the variations in creative thinking during various stages of a design project and the relation between creative thinking and motivation factors.

Searching for Information Online: Using Big Data to Identify the Concerns of Potential Army Recruits

DTIC Science & Technology

2016-01-01

software. For instance, such Internet search engines as Google or Yahoo! often gather anonymized data regarding the topics that people search for, as...suggesting that these and other information needs may be fur- ther reflected in usage of online search engines . Google makes aggregated and anonymized...Internet search engines such as Google or Yahoo! often gather anonymized data regarding the topics that people search for, as well as the date and

Index Relativity and Patron Search Strategy.

ERIC Educational Resources Information Center

Allison, DeeAnn; Childers Scott

2002-01-01

Describes a study at the University of Nebraska-Lincoln that compared searches in two different keyword indexes with similar content where search results were dependent on search strategy quality, search engine execution, and content. Results showed search engine execution had an impact on the number of matches and that users ignored search help…

An assessment of the visibility of MeSH-indexed medical web catalogs through search engines.

PubMed

Zweigenbaum, P; Darmoni, S J; Grabar, N; Douyère, M; Benichou, J

2002-01-01

Manually indexed Internet health catalogs such as CliniWeb or CISMeF provide resources for retrieving high-quality health information. Users of these quality-controlled subject gateways are most often referred to them by general search engines such as Google, AltaVista, etc. This raises several questions, among which the following: what is the relative visibility of medical Internet catalogs through search engines? This study addresses this issue by measuring and comparing the visibility of six major, MeSH-indexed health catalogs through four different search engines (AltaVista, Google, Lycos, Northern Light) in two languages (English and French). Over half a million queries were sent to the search engines; for most of these search engines, according to our measures at the time the queries were sent, the most visible catalog for English MeSH terms was CliniWeb and the most visible one for French MeSH terms was CISMeF.

Installation Restoration Program Phase 1: Records Search of Hanscom Air Force Base, Massachusetts

DTIC Science & Technology

1984-08-01

Engineer o Kevin R. Boyer, P.E., Project Manager and Civil Engineer o Alfred N. Wickline, Records Search Team Leader and Soil Scientist o Claudia A...INVESTIGATION TEAM :I.., 𔃾 44. ’m4, Use or disclosure of proposal data is subject to the restriction on the Title page of this Proposal. KEVIN R... KEVIN R. BOYER, P.E. Page 2 of 3 While working under the USEPA’s Field Investigation Team (FIT) program, Mr. Boyer was part of a quality assurance (QA

Internet Search Engines - Fluctuations in Document Accessibility.

ERIC Educational Resources Information Center

Mettrop, Wouter; Nieuwenhuysen, Paul

2001-01-01

Reports an empirical investigation of the consistency of retrieval through Internet search engines. Evaluates 13 engines: AltaVista, EuroFerret, Excite, HotBot, InfoSeek, Lycos, MSN, NorthernLight, Snap, WebCrawler, and three national Dutch engines: Ilse, Search.nl and Vindex. The focus is on a characteristic related to size: the degree of…

Developing a search engine for pharmacotherapeutic information that is not published in biomedical journals.

PubMed

Do Pazo-Oubiña, F; Calvo Pita, C; Puigventós Latorre, F; Periañez-Párraga, L; Ventayol Bosch, P

2011-01-01

To identify publishers of pharmacotherapeutic information not found in biomedical journals that focuses on evaluating and providing advice on medicines and to develop a search engine to access this information. Compiling web sites that publish information on the rational use of medicines and have no commercial interests. Free-access web sites in Spanish, Galician, Catalan or English. Designing a search engine using the Google "custom search" application. Overall 159 internet addresses were compiled and were classified into 9 labels. We were able to recover the information from the selected sources using a search engine, which is called "AlquimiA" and available from http://www.elcomprimido.com/FARHSD/AlquimiA.htm. The main sources of pharmacotherapeutic information not published in biomedical journals were identified. The search engine is a useful tool for searching and accessing "grey literature" on the internet. Copyright © 2010 SEFH. Published by Elsevier Espana. All rights reserved.

Index of Available Research on Military Impacts: Optimal Allocation of Land for Training and Non-training Uses

DTIC Science & Technology

2012-06-01

Center (now the “US Army Environmental Command”) USAF US Air Force USLE Universal Soil Loss Equation USPED Unit Stream Power Erosion and Deposition...and “ soil .” The previous analysis entered these search terms into the following data- base search engines and on-line library resources: • Web of...military vehicle impact,” “ soil ,” “vehicle,” “vehicle impact,” and “vehicle soil .” Search terms were selected based on the number of hits they returned in

Seeking Health Information Online: Does Wikipedia Matter?

PubMed Central

Laurent, Michaël R.; Vickers, Tim J.

2009-01-01

Objective To determine the significance of the English Wikipedia as a source of online health information. Design The authors measured Wikipedia's ranking on general Internet search engines by entering keywords from MedlinePlus, NHS Direct Online, and the National Organization of Rare Diseases as queries into search engine optimization software. We assessed whether article quality influenced this ranking. The authors tested whether traffic to Wikipedia coincided with epidemiological trends and news of emerging health concerns, and how it compares to MedlinePlus. Measurements Cumulative incidence and average position of Wikipedia® compared to other Web sites among the first 20 results on general Internet search engines (Google®, Google UK®, Yahoo®, and MSN®), and page view statistics for selected Wikipedia articles and MedlinePlus pages. Results Wikipedia ranked among the first ten results in 71–85% of search engines and keywords tested. Wikipedia surpassed MedlinePlus and NHS Direct Online (except for queries from the latter on Google UK), and ranked higher with quality articles. Wikipedia ranked highest for rare diseases, although its incidence in several categories decreased. Page views increased parallel to the occurrence of 20 seasonal disorders and news of three emerging health concerns. Wikipedia articles were viewed more often than MedlinePlus Topic (p = 0.001) but for MedlinePlus Encyclopedia pages, the trend was not significant (p = 0.07–0.10). Conclusions Based on its search engine ranking and page view statistics, the English Wikipedia is a prominent source of online health information compared to the other online health information providers studied. PMID:19390105

Improved Search Techniques

NASA Technical Reports Server (NTRS)

Albornoz, Caleb Ronald

2012-01-01

Thousands of millions of documents are stored and updated daily in the World Wide Web. Most of the information is not efficiently organized to build knowledge from the stored data. Nowadays, search engines are mainly used by users who rely on their skills to look for the information needed. This paper presents different techniques search engine users can apply in Google Search to improve the relevancy of search results. According to the Pew Research Center, the average person spends eight hours a month searching for the right information. For instance, a company that employs 1000 employees wastes $2.5 million dollars on looking for nonexistent and/or not found information. The cost is very high because decisions are made based on the information that is readily available to use. Whenever the information necessary to formulate an argument is not available or found, poor decisions may be made and mistakes will be more likely to occur. Also, the survey indicates that only 56% of Google users feel confident with their current search skills. Moreover, just 76% of the information that is available on the Internet is accurate.

The Impact of Subject Indexes on Semantic Indeterminacy in Enterprise Document Retrieval

ERIC Educational Resources Information Center

Schymik, Gregory

2012-01-01

Ample evidence exists to support the conclusion that enterprise search is failing its users. This failure is costing corporate America billions of dollars every year. Most enterprise search engines are built using web search engines as their foundations. These search engines are optimized for web use and are inadequate when used inside the…

The effective use of search engines on the Internet.

PubMed

Younger, P

This article explains how nurses can get the most out of researching information on the internet using the search engine Google. It also explores some of the other types of search engines that are available. Internet users are shown how to find text, images and reports and search within sites. Copyright issues are also discussed.

Practical Tips and Strategies for Finding Information on the Internet.

ERIC Educational Resources Information Center

Armstrong, Rhonda; Flanagan, Lynn

This paper presents the most important concepts and techniques to use in successfully searching the major World Wide Web search engines and directories, explains the basics of how search engines work, and describes what is included in their indexes. Following an introduction that gives an overview of Web directories and search engines, the first…

Do Seasons Have an Influence on the Incidence of Depression? The Use of an Internet Search Engine Query Data as a Proxy of Human Affect

PubMed Central

Yang, Albert C.; Huang, Norden E.; Peng, Chung-Kang; Tsai, Shih-Jen

2010-01-01

Background Seasonal depression has generated considerable clinical interest in recent years. Despite a common belief that people in higher latitudes are more vulnerable to low mood during the winter, it has never been demonstrated that human's moods are subject to seasonal change on a global scale. The aim of this study was to investigate large-scale seasonal patterns of depression using Internet search query data as a signature and proxy of human affect. Methodology/Principal Findings Our study was based on a publicly available search engine database, Google Insights for Search, which provides time series data of weekly search trends from January 1, 2004 to June 30, 2009. We applied an empirical mode decomposition method to isolate seasonal components of health-related search trends of depression in 54 geographic areas worldwide. We identified a seasonal trend of depression that was opposite between the northern and southern hemispheres; this trend was significantly correlated with seasonal oscillations of temperature (USA: r = −0.872, p<0.001; Australia: r = −0.656, p<0.001). Based on analyses of search trends over 54 geological locations worldwide, we found that the degree of correlation between searching for depression and temperature was latitude-dependent (northern hemisphere: r = −0.686; p<0.001; southern hemisphere: r = 0.871; p<0.0001). Conclusions/Significance Our findings indicate that Internet searches for depression from people in higher latitudes are more vulnerable to seasonal change, whereas this phenomenon is obscured in tropical areas. This phenomenon exists universally across countries, regardless of language. This study provides novel, Internet-based evidence for the epidemiology of seasonal depression. PMID:21060851

Search Tips

MedlinePlus

... do not need to use AND because the search engine automatically finds resources containing all of your search ... Use as a wildcard when you want the search engine to fill in the blank for you; you ...

Installation Restoration Program. Phase 1. Records Search 15th ABW Satellite Installations, Hawaii

DTIC Science & Technology

1984-09-01

Hickam POL Storage Facilities and Pipeline The POL storage facilities remotely located from Hickam Air Force Base (AFB...airfield with less activity than nearby Wheeler and Hickam Air Force Bases . Aircraft activity was significantly reduced in the late 1940’s and the...United States Air Force to conduct the Phase I Records Search at the 15th Air Base Wing 1-2 ES ENGINEERING-SCIENCE PHASE I PHASE 11 PHASE IV

PubMed vs. HighWire Press: a head-to-head comparison of two medical literature search engines.

PubMed

Vanhecke, Thomas E; Barnes, Michael A; Zimmerman, Janet; Shoichet, Sandor

2007-09-01

PubMed and HighWire Press are both useful medical literature search engines available for free to anyone on the internet. We measured retrieval accuracy, number of results generated, retrieval speed, features and search tools on HighWire Press and PubMed using the quick search features of each. We found that using HighWire Press resulted in a higher likelihood of retrieving the desired article and higher number of search results than the same search on PubMed. PubMed was faster than HighWire Press in delivering search results regardless of search settings. There are considerable differences in search features between these two search engines.

Dermatological image search engines on the Internet: do they work?

PubMed

Cutrone, M; Grimalt, R

2007-02-01

Atlases on CD-ROM first substituted the use of paediatric dermatology atlases printed on paper. This permitted a faster search and a practical comparison of differential diagnoses. The third step in the evolution of clinical atlases was the onset of the online atlas. Many doctors now use the Internet image search engines to obtain clinical images directly. The aim of this study was to test the reliability of the image search engines compared to the online atlases. We tested seven Internet image search engines with three paediatric dermatology diseases. In general, the service offered by the search engines is good, and continues to be free of charge. The coincidence between what we searched for and what we found was generally excellent, and contained no advertisements. Most Internet search engines provided similar results but some were more user friendly than others. It is not necessary to repeat the same research with Picsearch, Lycos and MSN, as the response would be the same; there is a possibility that they might share software. Image search engines are a useful, free and precise method to obtain paediatric dermatology images for teaching purposes. There is still the matter of copyright to be resolved. What are the legal uses of these 'free' images? How do we define 'teaching purposes'? New watermark methods and encrypted electronic signatures might solve these problems and answer these questions.

Computationally mapping sequence space to understand evolutionary protein engineering.

PubMed

Armstrong, Kathryn A; Tidor, Bruce

2008-01-01

Evolutionary protein engineering has been dramatically successful, producing a wide variety of new proteins with altered stability, binding affinity, and enzymatic activity. However, the success of such procedures is often unreliable, and the impact of the choice of protein, engineering goal, and evolutionary procedure is not well understood. We have created a framework for understanding aspects of the protein engineering process by computationally mapping regions of feasible sequence space for three small proteins using structure-based design protocols. We then tested the ability of different evolutionary search strategies to explore these sequence spaces. The results point to a non-intuitive relationship between the error-prone PCR mutation rate and the number of rounds of replication. The evolutionary relationships among feasible sequences reveal hub-like sequences that serve as particularly fruitful starting sequences for evolutionary search. Moreover, genetic recombination procedures were examined, and tradeoffs relating sequence diversity and search efficiency were identified. This framework allows us to consider the impact of protein structure on the allowed sequence space and therefore on the challenges that each protein presents to error-prone PCR and genetic recombination procedures.

Children's Search Engines from an Information Search Process Perspective.

ERIC Educational Resources Information Center

Broch, Elana

2000-01-01

Describes cognitive and affective characteristics of children and teenagers that may affect their Web searching behavior. Reviews literature on children's searching in online public access catalogs (OPACs) and using digital libraries. Profiles two Web search engines. Discusses some of the difficulties children have searching the Web, in the…

The Honeymoon Is Over: Leading the Way to Lasting Search Habits.

ERIC Educational Resources Information Center

Pierson, Melissa

1997-01-01

To become efficient Internet searchers, students and teachers need to learn online search skills. Discusses hierarchical subject directories (Yahoo) and search engines (Excite, Lycos, Alta Vista, HotBot); lists top search engines and their universal resource locators (URL). Provides examples of search strings; outlines search tips, and a…

FDRAnalysis: a tool for the integrated analysis of tandem mass spectrometry identification results from multiple search engines.

PubMed

Wedge, David C; Krishna, Ritesh; Blackhurst, Paul; Siepen, Jennifer A; Jones, Andrew R; Hubbard, Simon J

2011-04-01

Confident identification of peptides via tandem mass spectrometry underpins modern high-throughput proteomics. This has motivated considerable recent interest in the postprocessing of search engine results to increase confidence and calculate robust statistical measures, for example through the use of decoy databases to calculate false discovery rates (FDR). FDR-based analyses allow for multiple testing and can assign a single confidence value for both sets and individual peptide spectrum matches (PSMs). We recently developed an algorithm for combining the results from multiple search engines, integrating FDRs for sets of PSMs made by different search engine combinations. Here we describe a web-server and a downloadable application that makes this routinely available to the proteomics community. The web server offers a range of outputs including informative graphics to assess the confidence of the PSMs and any potential biases. The underlying pipeline also provides a basic protein inference step, integrating PSMs into protein ambiguity groups where peptides can be matched to more than one protein. Importantly, we have also implemented full support for the mzIdentML data standard, recently released by the Proteomics Standards Initiative, providing users with the ability to convert native formats to mzIdentML files, which are available to download.

FDRAnalysis: A tool for the integrated analysis of tandem mass spectrometry identification results from multiple search engines

PubMed Central

Wedge, David C; Krishna, Ritesh; Blackhurst, Paul; Siepen, Jennifer A; Jones, Andrew R.; Hubbard, Simon J.

2013-01-01

Confident identification of peptides via tandem mass spectrometry underpins modern high-throughput proteomics. This has motivated considerable recent interest in the post-processing of search engine results to increase confidence and calculate robust statistical measures, for example through the use of decoy databases to calculate false discovery rates (FDR). FDR-based analyses allow for multiple testing and can assign a single confidence value for both sets and individual peptide spectrum matches (PSMs). We recently developed an algorithm for combining the results from multiple search engines, integrating FDRs for sets of PSMs made by different search engine combinations. Here we describe a web-server, and a downloadable application, which makes this routinely available to the proteomics community. The web server offers a range of outputs including informative graphics to assess the confidence of the PSMs and any potential biases. The underlying pipeline provides a basic protein inference step, integrating PSMs into protein ambiguity groups where peptides can be matched to more than one protein. Importantly, we have also implemented full support for the mzIdentML data standard, recently released by the Proteomics Standards Initiative, providing users with the ability to convert native formats to mzIdentML files, which are available to download. PMID:21222473

Combining Search Engines for Comparative Proteomics

PubMed Central

Tabb, David

2012-01-01

Many proteomics laboratories have found spectral counting to be an ideal way to recognize biomarkers that differentiate cohorts of samples. This approach assumes that proteins that differ in quantity between samples will generate different numbers of identifiable tandem mass spectra. Increasingly, researchers are employing multiple search engines to maximize the identifications generated from data collections. This talk evaluates four strategies to combine information from multiple search engines in comparative proteomics. The “Count Sum” model pools the spectra across search engines. The “Vote Counting” model combines the judgments from each search engine by protein. Two other models employ parametric and non-parametric analyses of protein-specific p-values from different search engines. We evaluated the four strategies in two different data sets. The ABRF iPRG 2009 study generated five LC-MS/MS analyses of “red” E. coli and five analyses of “yellow” E. coli. NCI CPTAC Study 6 generated five concentrations of Sigma UPS1 spiked into a yeast background. All data were identified with X!Tandem, Sequest, MyriMatch, and TagRecon. For both sample types, “Vote Counting” appeared to manage the diverse identification sets most effectively, yielding heightened discrimination as more search engines were added.

Qualitative assessment of online information about age-related macular degeneration available in Portuguese.

PubMed

Agi, Jorge; Kasahara, Niro; Lottenberg, Claudio Luiz

2018-06-07

To evaluate the quality of online information on age-related macular degeneration available in Portuguese. The search term "age-related macular degeneration" was used to browse the web using four different search engines. The first 40 websites appearing on match lists provided by each search engine were recorded and those listed in at least three tab pages selected. The Sandvik Severity Index was used as to assess website quality. Quality of information available on selected websites was rated average (mean Sandvik Score 7.08±2.23). Most websites disseminating information about age-related macular degeneration were of average quality. The need to readjust web-based information to target lay public and promote increased understanding was emphasized.

Engineering Your Job Search: A Job-Finding Resource for Engineering Professionals.

ERIC Educational Resources Information Center

1995

This guide, which is intended for engineering professionals, explains how to use up-to-date job search techniques to design and conduct an effective job hunt. The first 11 chapters discuss the following steps in searching for a job: handling a job loss; managing time and financial resources while conducting a full-time job search; using objective…

Query Transformations for Result Merging

DTIC Science & Technology

2014-11-01

tors, term dependence, query expansion 1. INTRODUCTION Federated search deals with the problem of aggregating results from multiple search engines . The...invidual search engines are (i) typically focused on a particular domain or a particular corpus, (ii) employ diverse retrieval models, and (iii...determine which search engines are appropri- ate for addressing the information need (resource selection), and (ii) merging the results returned by

Effective Approaches to Motivate and Engage Reluctant Boys in Literacy

ERIC Educational Resources Information Center

Senn, Nicole

2012-01-01

The purpose of this article was to investigate the reasons why elementary-aged boys often lack motivation in literacy and to provide teachers with useful approaches to engage reluctant boys in reading and writing. Following a comprehensive search of multiple university data base search engines, the author critically evaluated 21 peer-reviewed…

Systematically Identifying Relevant Research: Case Study on Child Protection Social Workers' Resilience

ERIC Educational Resources Information Center

McFadden, Paula; Taylor, Brian J.; Campbell, Anne; McQuilkin, Janice

2012-01-01

Context: The development of a consolidated knowledge base for social work requires rigorous approaches to identifying relevant research. Method: The quality of 10 databases and a web search engine were appraised by systematically searching for research articles on resilience and burnout in child protection social workers. Results: Applied Social…

Online World Conference and Expo: A Zillion Things at Once.

ERIC Educational Resources Information Center

Chuck, Lysbeth B.

1997-01-01

Presents the keynote speakers of the Online World 1997 conference, as well as HotBot and other search engines, the CyberClinic tracks (Practical Searching, Resource Management, Trends and Technology, Corporate Electronic Publishing, Content Reviews, and Roundtable Discussions), Web-based communities, and an exhibited database of over 12,000…

Probabilistic consensus scoring improves tandem mass spectrometry peptide identification.

PubMed

Nahnsen, Sven; Bertsch, Andreas; Rahnenführer, Jörg; Nordheim, Alfred; Kohlbacher, Oliver

2011-08-05

Database search is a standard technique for identifying peptides from their tandem mass spectra. To increase the number of correctly identified peptides, we suggest a probabilistic framework that allows the combination of scores from different search engines into a joint consensus score. Central to the approach is a novel method to estimate scores for peptides not found by an individual search engine. This approach allows the estimation of p-values for each candidate peptide and their combination across all search engines. The consensus approach works better than any single search engine across all different instrument types considered in this study. Improvements vary strongly from platform to platform and from search engine to search engine. Compared to the industry standard MASCOT, our approach can identify up to 60% more peptides. The software for consensus predictions is implemented in C++ as part of OpenMS, a software framework for mass spectrometry. The source code is available in the current development version of OpenMS and can easily be used as a command line application or via a graphical pipeline designer TOPPAS.

Sagace: A web-based search engine for biomedical databases in Japan

PubMed Central

2012-01-01

Background In the big data era, biomedical research continues to generate a large amount of data, and the generated information is often stored in a database and made publicly available. Although combining data from multiple databases should accelerate further studies, the current number of life sciences databases is too large to grasp features and contents of each database. Findings We have developed Sagace, a web-based search engine that enables users to retrieve information from a range of biological databases (such as gene expression profiles and proteomics data) and biological resource banks (such as mouse models of disease and cell lines). With Sagace, users can search more than 300 databases in Japan. Sagace offers features tailored to biomedical research, including manually tuned ranking, a faceted navigation to refine search results, and rich snippets constructed with retrieved metadata for each database entry. Conclusions Sagace will be valuable for experts who are involved in biomedical research and drug development in both academia and industry. Sagace is freely available at http://sagace.nibio.go.jp/en/. PMID:23110816

Human Flesh Search Engine and Online Privacy.

PubMed

Zhang, Yang; Gao, Hong

2016-04-01

Human flesh search engine can be a double-edged sword, bringing convenience on the one hand and leading to infringement of personal privacy on the other hand. This paper discusses the ethical problems brought about by the human flesh search engine, as well as possible solutions.

An assessment of the visibility of MeSH-indexed medical web catalogs through search engines.

PubMed Central

Zweigenbaum, P.; Darmoni, S. J.; Grabar, N.; Douyère, M.; Benichou, J.

2002-01-01

Manually indexed Internet health catalogs such as CliniWeb or CISMeF provide resources for retrieving high-quality health information. Users of these quality-controlled subject gateways are most often referred to them by general search engines such as Google, AltaVista, etc. This raises several questions, among which the following: what is the relative visibility of medical Internet catalogs through search engines? This study addresses this issue by measuring and comparing the visibility of six major, MeSH-indexed health catalogs through four different search engines (AltaVista, Google, Lycos, Northern Light) in two languages (English and French). Over half a million queries were sent to the search engines; for most of these search engines, according to our measures at the time the queries were sent, the most visible catalog for English MeSH terms was CliniWeb and the most visible one for French MeSH terms was CISMeF. PMID:12463965

Toward building a comprehensive data mart

NASA Astrophysics Data System (ADS)

Boulware, Douglas; Salerno, John; Bleich, Richard; Hinman, Michael L.

2004-04-01

To uncover new relationships or patterns one must first build a corpus of data or what some call a data mart. How can we make sure we have collected all the pertinent data and have maximized coverage? There are hundreds of search engines that are available for use on the Internet today. Which one is best? Is one better for one problem and a second better for another? Are meta-search engines better than individual search engines? In this paper we look at one possible approach in developing a methodology to compare a number of search engines. Before we present this methodology, we first provide our motivation towards the need for increased coverage. We next investigate how we can obtain ground truth and what the ground truth can provide us in the way of some insight into the Internet and search engine capabilities. We then conclude our discussion by developing a methodology in which we compare a number of the search engines and how we can increase overall coverage and thus a more comprehensive data mart.

In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics.

PubMed

Audain, Enrique; Uszkoreit, Julian; Sachsenberg, Timo; Pfeuffer, Julianus; Liang, Xiao; Hermjakob, Henning; Sanchez, Aniel; Eisenacher, Martin; Reinert, Knut; Tabb, David L; Kohlbacher, Oliver; Perez-Riverol, Yasset

2017-01-06

In mass spectrometry-based shotgun proteomics, protein identifications are usually the desired result. However, most of the analytical methods are based on the identification of reliable peptides and not the direct identification of intact proteins. Thus, assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is a critical step in proteomics research. Currently, different protein inference algorithms and tools are available for the proteomics community. Here, we evaluated five software tools for protein inference (PIA, ProteinProphet, Fido, ProteinLP, MSBayesPro) using three popular database search engines: Mascot, X!Tandem, and MS-GF+. All the algorithms were evaluated using a highly customizable KNIME workflow using four different public datasets with varying complexities (different sample preparation, species and analytical instruments). We defined a set of quality control metrics to evaluate the performance of each combination of search engines, protein inference algorithm, and parameters on each dataset. We show that the results for complex samples vary not only regarding the actual numbers of reported protein groups but also concerning the actual composition of groups. Furthermore, the robustness of reported proteins when using databases of differing complexities is strongly dependant on the applied inference algorithm. Finally, merging the identifications of multiple search engines does not necessarily increase the number of reported proteins, but does increase the number of peptides per protein and thus can generally be recommended. Protein inference is one of the major challenges in MS-based proteomics nowadays. Currently, there are a vast number of protein inference algorithms and implementations available for the proteomics community. Protein assembly impacts in the final results of the research, the quantitation values and the final claims in the research manuscript. Even though protein inference is a crucial step in proteomics data analysis, a comprehensive evaluation of the many different inference methods has never been performed. Previously Journal of proteomics has published multiple studies about other benchmark of bioinformatics algorithms (PMID: 26585461; PMID: 22728601) in proteomics studies making clear the importance of those studies for the proteomics community and the journal audience. This manuscript presents a new bioinformatics solution based on the KNIME/OpenMS platform that aims at providing a fair comparison of protein inference algorithms (https://github.com/KNIME-OMICS). Six different algorithms - ProteinProphet, MSBayesPro, ProteinLP, Fido and PIA- were evaluated using the highly customizable workflow on four public datasets with varying complexities. Five popular database search engines Mascot, X!Tandem, MS-GF+ and combinations thereof were evaluated for every protein inference tool. In total >186 proteins lists were analyzed and carefully compare using three metrics for quality assessments of the protein inference results: 1) the numbers of reported proteins, 2) peptides per protein, and the 3) number of uniquely reported proteins per inference method, to address the quality of each inference method. We also examined how many proteins were reported by choosing each combination of search engines, protein inference algorithms and parameters on each dataset. The results show that using 1) PIA or Fido seems to be a good choice when studying the results of the analyzed workflow, regarding not only the reported proteins and the high-quality identifications, but also the required runtime. 2) Merging the identifications of multiple search engines gives almost always more confident results and increases the number of peptides per protein group. 3) The usage of databases containing not only the canonical, but also known isoforms of proteins has a small impact on the number of reported proteins. The detection of specific isoforms could, concerning the question behind the study, compensate for slightly shorter reports using the parsimonious reports. 4) The current workflow can be easily extended to support new algorithms and search engine combinations. Copyright © 2016. Published by Elsevier B.V.

EMERSE: The Electronic Medical Record Search Engine

PubMed Central

Hanauer, David A.

2006-01-01

EMERSE (The Electronic Medical Record Search Engine) is an intuitive, powerful search engine for free-text documents in the electronic medical record. It offers multiple options for creating complex search queries yet has an interface that is easy enough to be used by those with minimal computer experience. EMERSE is ideal for retrospective chart reviews and data abstraction and may have potential for clinical care as well.

Tags Extarction from Spatial Documents in Search Engines

NASA Astrophysics Data System (ADS)

Borhaninejad, S.; Hakimpour, F.; Hamzei, E.

2015-12-01

Nowadays the selective access to information on the Web is provided by search engines, but in the cases which the data includes spatial information the search task becomes more complex and search engines require special capabilities. The purpose of this study is to extract the information which lies in spatial documents. To that end, we implement and evaluate information extraction from GML documents and a retrieval method in an integrated approach. Our proposed system consists of three components: crawler, database and user interface. In crawler component, GML documents are discovered and their text is parsed for information extraction; storage. The database component is responsible for indexing of information which is collected by crawlers. Finally the user interface component provides the interaction between system and user. We have implemented this system as a pilot system on an Application Server as a simulation of Web. Our system as a spatial search engine provided searching capability throughout the GML documents and thus an important step to improve the efficiency of search engines has been taken.

Smart internet search engine through 6W

NASA Astrophysics Data System (ADS)

Goehler, Stephen; Cader, Masud; Szu, Harold

2006-04-01

Current Internet search engine technology is limited in its ability to display necessary relevant information to the user. Yahoo, Google and Microsoft use lookup tables or indexes which limits the ability of users to find their desired information. While these companies have improved their results over the years by enhancing their existing technology and algorithms with specialized heuristics such as PageRank, there is a need for a next generation smart search engine that can effectively interpret the relevance of user searches and provide the actual information requested. This paper explores whether a smarter Internet search engine can effectively fulfill a user's needs through the use of 6W representations.

Web Search Studies: Multidisciplinary Perspectives on Web Search Engines

NASA Astrophysics Data System (ADS)

Zimmer, Michael

Perhaps the most significant tool of our internet age is the web search engine, providing a powerful interface for accessing the vast amount of information available on the world wide web and beyond. While still in its infancy compared to the knowledge tools that precede it - such as the dictionary or encyclopedia - the impact of web search engines on society and culture has already received considerable attention from a variety of academic disciplines and perspectives. This article aims to organize a meta-discipline of “web search studies,” centered around a nucleus of major research on web search engines from five key perspectives: technical foundations and evaluations; transaction log analyses; user studies; political, ethical, and cultural critiques; and legal and policy analyses.

Analysis of Online Information Searching for Cardiovascular Diseases on a Consumer Health Information Portal

PubMed Central

Jadhav, Ashutosh; Sheth, Amit; Pathak, Jyotishman

2014-01-01

Since the early 2000’s, Internet usage for health information searching has increased significantly. Studying search queries can help us to understand users “information need” and how do they formulate search queries (“expression of information need”). Although cardiovascular diseases (CVD) affect a large percentage of the population, few studies have investigated how and what users search for CVD. We address this knowledge gap in the community by analyzing a large corpus of 10 million CVD related search queries from MayoClinic.com. Using UMLS MetaMap and UMLS semantic types/concepts, we developed a rule-based approach to categorize the queries into 14 health categories. We analyzed structural properties, types (keyword-based/Wh-questions/Yes-No questions) and linguistic structure of the queries. Our results show that the most searched health categories are ‘Diseases/Conditions’, ‘Vital-Sings’, ‘Symptoms’ and ‘Living-with’. CVD queries are longer and are predominantly keyword-based. This study extends our knowledge about online health information searching and provides useful insights for Web search engines and health websites. PMID:25954380

Determination of geographic variance in stroke prevalence using Internet search engine analytics.

PubMed

Walcott, Brian P; Nahed, Brian V; Kahle, Kristopher T; Redjal, Navid; Coumans, Jean-Valery

2011-06-01

Previous methods to determine stroke prevalence, such as nationwide surveys, are labor-intensive endeavors. Recent advances in search engine query analytics have led to a new metric for disease surveillance to evaluate symptomatic phenomenon, such as influenza. The authors hypothesized that the use of search engine query data can determine the prevalence of stroke. The Google Insights for Search database was accessed to analyze anonymized search engine query data. The authors' search strategy utilized common search queries used when attempting either to identify the signs and symptoms of a stroke or to perform stroke education. The search logic was as follows: (stroke signs + stroke symptoms + mini stroke--heat) from January 1, 2005, to December 31, 2010. The relative number of searches performed (the interest level) for this search logic was established for all 50 states and the District of Columbia. A Pearson product-moment correlation coefficient was calculated from the statespecific stroke prevalence data previously reported. Web search engine interest level was available for all 50 states and the District of Columbia over the time period for January 1, 2005-December 31, 2010. The interest level was highest in Alabama and Tennessee (100 and 96, respectively) and lowest in California and Virginia (58 and 53, respectively). The Pearson correlation coefficient (r) was calculated to be 0.47 (p = 0.0005, 2-tailed). Search engine query data analysis allows for the determination of relative stroke prevalence. Further investigation will reveal the reliability of this metric to determine temporal pattern analysis and prevalence in this and other symptomatic diseases.

A two-level cache for distributed information retrieval in search engines.

PubMed

Zhang, Weizhe; He, Hui; Ye, Jianwei

2013-01-01

To improve the performance of distributed information retrieval in search engines, we propose a two-level cache structure based on the queries of the users' logs. We extract the highest rank queries of users from the static cache, in which the queries are the most popular. We adopt the dynamic cache as an auxiliary to optimize the distribution of the cache data. We propose a distribution strategy of the cache data. The experiments prove that the hit rate, the efficiency, and the time consumption of the two-level cache have advantages compared with other structures of cache.

A Two-Level Cache for Distributed Information Retrieval in Search Engines

PubMed Central

Zhang, Weizhe; He, Hui; Ye, Jianwei

2013-01-01

To improve the performance of distributed information retrieval in search engines, we propose a two-level cache structure based on the queries of the users' logs. We extract the highest rank queries of users from the static cache, in which the queries are the most popular. We adopt the dynamic cache as an auxiliary to optimize the distribution of the cache data. We propose a distribution strategy of the cache data. The experiments prove that the hit rate, the efficiency, and the time consumption of the two-level cache have advantages compared with other structures of cache. PMID:24363621

Semantic Clustering of Search Engine Results

PubMed Central

Soliman, Sara Saad; El-Sayed, Maged F.; Hassan, Yasser F.

2015-01-01

This paper presents a novel approach for search engine results clustering that relies on the semantics of the retrieved documents rather than the terms in those documents. The proposed approach takes into consideration both lexical and semantics similarities among documents and applies activation spreading technique in order to generate semantically meaningful clusters. This approach allows documents that are semantically similar to be clustered together rather than clustering documents based on similar terms. A prototype is implemented and several experiments are conducted to test the prospered solution. The result of the experiment confirmed that the proposed solution achieves remarkable results in terms of precision. PMID:26933673

Roogle: an information retrieval engine for clinical data warehouse.

PubMed

Cuggia, Marc; Garcelon, Nicolas; Campillo-Gimenez, Boris; Bernicot, Thomas; Laurent, Jean-François; Garin, Etienne; Happe, André; Duvauferrier, Régis

2011-01-01

High amount of relevant information is contained in reports stored in the electronic patient records and associated metadata. R-oogle is a project aiming at developing information retrieval engines adapted to these reports and designed for clinicians. The system consists in a data warehouse (full-text reports and structured data) imported from two different hospital information systems. Information retrieval is performed using metadata-based semantic and full-text search methods (as Google). Applications may be biomarkers identification in a translational approach, search of specific cases, and constitution of cohorts, professional practice evaluation, and quality control assessment.

Where people look for online health information.

PubMed

LaValley, Susan A; Kiviniemi, Marc T; Gage-Bouchard, Elizabeth A

2017-06-01

To identify health-related websites Americans are using, demographic characteristics associated with certain website type and how website type shapes users' online information seeking experiences. Data from the Health Information National Trends Survey 4 Cycle 1 were used. User-identified websites were categorised into four types: government sponsored, commercially based, academically affiliated and search engines. Logistic regression analyses examined associations between users' sociodemographic characteristics and website type, and associations between website type and information search experience. Respondents reported using: commercial websites (71.8%), followed by a search engines (11.6%), academically affiliated sites (11.1%) and government-sponsored websites (5.5%). Older age was associated with the use of academic websites (OR 1.03, 95% CI 1.02, 1.04); younger age with commercial website use (OR 0.97, 95% CI 0.95, 0.98). Search engine use predicted increased levels of frustration, effort and concern over website information quality, while commercial website use predicted decreased levels of these same measures. Health information seekers experience varying levels of frustration, effort and concern related to their online searching. There is a need for continued efforts by librarians and health care professionals to train seekers of online health information to select websites using established guidelines and quality criteria. © 2016 Health Libraries Group.

BioTCM-SE: a semantic search engine for the information retrieval of modern biology and traditional Chinese medicine.

PubMed

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

BioTCM-SE: A Semantic Search Engine for the Information Retrieval of Modern Biology and Traditional Chinese Medicine

PubMed Central

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM. PMID:24772189

An Improved Forensic Science Information Search.

PubMed

Teitelbaum, J

2015-01-01

Although thousands of search engines and databases are available online, finding answers to specific forensic science questions can be a challenge even to experienced Internet users. Because there is no central repository for forensic science information, and because of the sheer number of disciplines under the forensic science umbrella, forensic scientists are often unable to locate material that is relevant to their needs. The author contends that using six publicly accessible search engines and databases can produce high-quality search results. The six resources are Google, PubMed, Google Scholar, Google Books, WorldCat, and the National Criminal Justice Reference Service. Carefully selected keywords and keyword combinations, designating a keyword phrase so that the search engine will search on the phrase and not individual keywords, and prompting search engines to retrieve PDF files are among the techniques discussed. Copyright © 2015 Central Police University.

Interactive Information Organization: Techniques and Evaluation

DTIC Science & Technology

2001-05-01

information search and access. Locating interesting information on the World Wide Web is the main task of on-line search engines . Such engines accept a...likelihood of being relevant to the user’s request. The majority of today’s Web search engines follow this scenario. The ordering of documents in the

Putting Google Scholar to the Test: A Preliminary Study

ERIC Educational Resources Information Center

Robinson, Mary L.; Wusteman, Judith

2007-01-01

Purpose: To describe a small-scale quantitative evaluation of the scholarly information search engine, Google Scholar. Design/methodology/approach: Google Scholar's ability to retrieve scholarly information was compared to that of three popular search engines: Ask.com, Google and Yahoo! Test queries were presented to all four search engines and…

Social media networking: YouTube and search engine optimization.

PubMed

Jackson, Rem; Schneider, Andrew; Baum, Neil

2011-01-01

This is the third part of a three-part article on social media networking. This installment will focus on YouTube and search engine optimization. This article will explore the application of YouTube to the medical practice and how YouTube can help a practice retain its existing patients and attract new patients to the practice. The article will also describe the importance of search engine optimization and how to make your content appear on the first page of the search engines such as Google, Yahoo, and YouTube.

Searching for American Indian Resources on the Internet.

ERIC Educational Resources Information Center

Pollack, Ira; Derby, Amy

This paper provides basic information on searching the Internet and lists World Wide Web sites containing resources for American Indian education. Comprehensive and topical Web directories, search engines, and meta-search engines are briefly described. Search strategies are discussed, and seven Web sites are listed that provide more advanced…

EMERSE: The Electronic Medical Record Search Engine

PubMed Central

Hanauer, David A.

2006-01-01

EMERSE (The Electronic Medical Record Search Engine) is an intuitive, powerful search engine for free-text documents in the electronic medical record. It offers multiple options for creating complex search queries yet has an interface that is easy enough to be used by those with minimal computer experience. EMERSE is ideal for retrospective chart reviews and data abstraction and may have potential for clinical care as well. PMID:17238560

In Search of a Better Search Engine

ERIC Educational Resources Information Center

Kolowich, Steve

2009-01-01

Early this decade, the number of Web-based documents stored on the servers of the University of Florida hovered near 300,000. By the end of 2006, that number had leapt to four million. Two years later, the university hosts close to eight million Web documents. Web sites for colleges and universities everywhere have become repositories for data…

[On the seasonality of dermatoses: a retrospective analysis of search engine query data depending on the season].

PubMed

Köhler, M J; Springer, S; Kaatz, M

2014-09-01

The volume of search engine queries about disease-relevant items reflects public interest and correlates with disease prevalence as proven by the example of flu (influenza). Other influences include media attention or holidays. The present work investigates if the seasonality of prevalence or symptom severity of dermatoses correlates with search engine query data. The relative weekly volume of dermatological relevant search terms was assessed by the online tool Google Trends for the years 2009-2013. For each item, the degree of seasonality was calculated via frequency analysis and a geometric approach. Many dermatoses show a marked seasonality, reflected by search engine query volumes. Unexpected seasonal variations of these queries suggest a previously unknown variability of the respective disease prevalence. Furthermore, using the example of allergic rhinitis, a close correlation of search engine query data with actual pollen count can be demonstrated. In many cases, search engine query data are appropriate to estimate seasonal variability in prevalence of common dermatoses. This finding may be useful for real-time analysis and formation of hypotheses concerning pathogenetic or symptom aggravating mechanisms and may thus contribute to improvement of diagnostics and prevention of skin diseases.

Pure random search for ambient sensor distribution optimisation in a smart home environment.

PubMed

Poland, Michael P; Nugent, Chris D; Wang, Hui; Chen, Liming

2011-01-01

Smart homes are living spaces facilitated with technology to allow individuals to remain in their own homes for longer, rather than be institutionalised. Sensors are the fundamental physical layer with any smart home, as the data they generate is used to inform decision support systems, facilitating appropriate actuator actions. Positioning of sensors is therefore a fundamental characteristic of a smart home. Contemporary smart home sensor distribution is aligned to either a) a total coverage approach; b) a human assessment approach. These methods for sensor arrangement are not data driven strategies, are unempirical and frequently irrational. This Study hypothesised that sensor deployment directed by an optimisation method that utilises inhabitants' spatial frequency data as the search space, would produce more optimal sensor distributions vs. the current method of sensor deployment by engineers. Seven human engineers were tasked to create sensor distributions based on perceived utility for 9 deployment scenarios. A Pure Random Search (PRS) algorithm was then tasked to create matched sensor distributions. The PRS method produced superior distributions in 98.4% of test cases (n=64) against human engineer instructed deployments when the engineers had no access to the spatial frequency data, and in 92.0% of test cases (n=64) when engineers had full access to these data. These results thus confirmed the hypothesis.

Qualitative assessment of online information about age-related macular degeneration available in Portuguese

PubMed Central

Agi, Jorge; Kasahara, Niro; Lottenberg, Claudio Luiz

2018-01-01

ABSTRACT Objective: To evaluate the quality of online information on age-related macular degeneration available in Portuguese. Methods: The search term “age-related macular degeneration” was used to browse the web using four different search engines. The first 40 websites appearing on match lists provided by each search engine were recorded and those listed in at least three tab pages selected. The Sandvik Severity Index was used as to assess website quality. Results: Quality of information available on selected websites was rated average (mean Sandvik Score 7.08±2.23). Conclusion: Most websites disseminating information about age-related macular degeneration were of average quality. The need to readjust web-based information to target lay public and promote increased understanding was emphasized. PMID:29898089

Searching for suicide-related information on Chinese websites.

PubMed

Chen, Ying-Yeh; Hung, Galen Chin-Lun; Cheng, Qijin; Tsai, Chi-Wei; Wu, Kevin Chien-Chang

2017-12-01

Growing concerns about cyber-suicide have prompted many studies on suicide information available on the web. However, very few studies have considered non-English websites. We aimed to analyze online suicide-related information accessed through Chinese-language websites. We used Taiwan's two most popular search engines (Google and Yahoo) to explore the results returned from six suicide-related search terms in March 2016. The first three pages listing the results from each search were analyzed and rated based on the attitude towards suicide (pro-suicide, anti-suicide, neutral/mixed, not a suicide site, or error). Comparisons across different search terms were also performed. In all, 375 linked webpages were included; 16.3% of the webpages were pro-suicide and 41.3% were anti-suicide. The majority of the pro-suicide sites were user-generated webpages (96.7%). Searches using the keywords 'ways to kill yourself' (31.7%) and 'painless suicide' (28.3%) generated much larger numbers of harmful webpages than the term 'suicide' (4.3%). We conclude that collaborative efforts with internet service providers and search engines to improve the ranking of anti-suicide webpages and websites and implement online suicide reporting guidelines are highly encouraged. Copyright © 2017 Elsevier B.V. All rights reserved.

FindZebra: a search engine for rare diseases.

PubMed

Dragusin, Radu; Petcu, Paula; Lioma, Christina; Larsen, Birger; Jørgensen, Henrik L; Cox, Ingemar J; Hansen, Lars Kai; Ingwersen, Peter; Winther, Ole

2013-06-01

The web has become a primary information resource about illnesses and treatments for both medical and non-medical users. Standard web search is by far the most common interface to this information. It is therefore of interest to find out how well web search engines work for diagnostic queries and what factors contribute to successes and failures. Among diseases, rare (or orphan) diseases represent an especially challenging and thus interesting class to diagnose as each is rare, diverse in symptoms and usually has scattered resources associated with it. We design an evaluation approach for web search engines for rare disease diagnosis which includes 56 real life diagnostic cases, performance measures, information resources and guidelines for customising Google Search to this task. In addition, we introduce FindZebra, a specialized (vertical) rare disease search engine. FindZebra is powered by open source search technology and uses curated freely available online medical information. FindZebra outperforms Google Search in both default set-up and customised to the resources used by FindZebra. We extend FindZebra with specialized functionalities exploiting medical ontological information and UMLS medical concepts to demonstrate different ways of displaying the retrieved results to medical experts. Our results indicate that a specialized search engine can improve the diagnostic quality without compromising the ease of use of the currently widely popular standard web search. The proposed evaluation approach can be valuable for future development and benchmarking. The FindZebra search engine is available at http://www.findzebra.com/. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

How To Do Field Searching in Web Search Engines: A Field Trip.

ERIC Educational Resources Information Center

Hock, Ran

1998-01-01

Describes the field search capabilities of selected Web search engines (AltaVista, HotBot, Infoseek, Lycos, Yahoo!) and includes a chart outlining what fields (date, title, URL, images, audio, video, links, page depth) are searchable, where to go on the page to search them, the syntax required (if any), and how field search queries are entered.…

EIIS: An Educational Information Intelligent Search Engine Supported by Semantic Services

ERIC Educational Resources Information Center

Huang, Chang-Qin; Duan, Ru-Lin; Tang, Yong; Zhu, Zhi-Ting; Yan, Yong-Jian; Guo, Yu-Qing

2011-01-01

The semantic web brings a new opportunity for efficient information organization and search. To meet the special requirements of the educational field, this paper proposes an intelligent search engine enabled by educational semantic support service, where three kinds of searches are integrated into Educational Information Intelligent Search (EIIS)…

MetaSpider: Meta-Searching and Categorization on the Web.

ERIC Educational Resources Information Center

Chen, Hsinchun; Fan, Haiyan; Chau, Michael; Zeng, Daniel

2001-01-01

Discusses the difficulty of locating relevant information on the Web and studies two approaches to addressing the low precision and poor presentation of search results: meta-search and document categorization. Introduces MetaSpider, a meta-search engine, and presents results of a user evaluation study that compared three search engines.…

What do patients know about their low back pain? An analysis of the quality of information available on the Internet.

PubMed

Galbusera, Fabio; Brayda-Bruno, Marco; Freutel, Maren; Seitz, Andreas; Steiner, Malte; Wehrle, Esther; Wilke, Hans-Joachim

2012-01-01

Previous surveys showed a poor quality of the web sites providing health information about low back pain. However, the rapid and continuous evolution of the Internet content may question the current validity of those investigations. The present study is aimed to quantitatively assess the quality of the Internet information about low back pain retrieved with the most commonly employed search engines. An Internet search with the keywords "low back pain" has been performed with Google, Yahoo!® and Bing™ in the English language. The top 30 hits obtained with each search engine were evaluated by five independent raters and averaged following criteria derived from previous works. All search results were categorized as declaring compliant to a quality standard for health information (e.g. HONCode) or not and based on the web site type (Institutional, Free informative, Commercial, News, Social Network, Unknown). The quality of the hits retrieved by the three search engines was extremely similar. The web sites had a clear purpose, were easy to navigate, and mostly lacked in validity and quality of the provided links. The conformity to a quality standard was correlated with a marked greater quality of the web sites in all respects. Institutional web sites had the best validity and ease of use. Free informative web sites had good quality but a markedly lower validity compared to Institutional websites. Commercial web sites provided more biased information. News web sites were well designed and easy to use, but lacked in validity. The average quality of the hits retrieved by the most commonly employed search engines could be defined as satisfactory and favorably comparable with previous investigations. Awareness of the user about checking the quality of the information remains of concern.

World Wide Web Based Image Search Engine Using Text and Image Content Features

NASA Astrophysics Data System (ADS)

Luo, Bo; Wang, Xiaogang; Tang, Xiaoou

2003-01-01

Using both text and image content features, a hybrid image retrieval system for Word Wide Web is developed in this paper. We first use a text-based image meta-search engine to retrieve images from the Web based on the text information on the image host pages to provide an initial image set. Because of the high-speed and low cost nature of the text-based approach, we can easily retrieve a broad coverage of images with a high recall rate and a relatively low precision. An image content based ordering is then performed on the initial image set. All the images are clustered into different folders based on the image content features. In addition, the images can be re-ranked by the content features according to the user feedback. Such a design makes it truly practical to use both text and image content for image retrieval over the Internet. Experimental results confirm the efficiency of the system.

Short-term Internet search using makes people rely on search engines when facing unknown issues.

PubMed

Wang, Yifan; Wu, Lingdan; Luo, Liang; Zhang, Yifen; Dong, Guangheng

2017-01-01

The Internet search engines, which have powerful search/sort functions and ease of use features, have become an indispensable tool for many individuals. The current study is to test whether the short-term Internet search training can make people more dependent on it. Thirty-one subjects out of forty subjects completed the search training study which included a pre-test, a six-day's training of Internet search, and a post-test. During the pre- and post- tests, subjects were asked to search online the answers to 40 unusual questions, remember the answers and recall them in the scanner. Un-learned questions were randomly presented at the recalling stage in order to elicited search impulse. Comparing to the pre-test, subjects in the post-test reported higher impulse to use search engines to answer un-learned questions. Consistently, subjects showed higher brain activations in dorsolateral prefrontal cortex and anterior cingulate cortex in the post-test than in the pre-test. In addition, there were significant positive correlations self-reported search impulse and brain responses in the frontal areas. The results suggest that a simple six-day's Internet search training can make people dependent on the search tools when facing unknown issues. People are easily dependent on the Internet search engines.

Short-term Internet search using makes people rely on search engines when facing unknown issues

PubMed Central

Wang, Yifan; Wu, Lingdan; Luo, Liang; Zhang, Yifen

2017-01-01

The Internet search engines, which have powerful search/sort functions and ease of use features, have become an indispensable tool for many individuals. The current study is to test whether the short-term Internet search training can make people more dependent on it. Thirty-one subjects out of forty subjects completed the search training study which included a pre-test, a six-day’s training of Internet search, and a post-test. During the pre- and post- tests, subjects were asked to search online the answers to 40 unusual questions, remember the answers and recall them in the scanner. Un-learned questions were randomly presented at the recalling stage in order to elicited search impulse. Comparing to the pre-test, subjects in the post-test reported higher impulse to use search engines to answer un-learned questions. Consistently, subjects showed higher brain activations in dorsolateral prefrontal cortex and anterior cingulate cortex in the post-test than in the pre-test. In addition, there were significant positive correlations self-reported search impulse and brain responses in the frontal areas. The results suggest that a simple six-day’s Internet search training can make people dependent on the search tools when facing unknown issues. People are easily dependent on the Internet search engines. PMID:28441408

Estimating Influenza Outbreaks Using Both Search Engine Query Data and Social Media Data in South Korea.

PubMed

Woo, Hyekyung; Cho, Youngtae; Shim, Eunyoung; Lee, Jong-Koo; Lee, Chang-Gun; Kim, Seong Hwan

2016-07-04

As suggested as early as in 2006, logs of queries submitted to search engines seeking information could be a source for detection of emerging influenza epidemics if changes in the volume of search queries are monitored (infodemiology). However, selecting queries that are most likely to be associated with influenza epidemics is a particular challenge when it comes to generating better predictions. In this study, we describe a methodological extension for detecting influenza outbreaks using search query data; we provide a new approach for query selection through the exploration of contextual information gleaned from social media data. Additionally, we evaluate whether it is possible to use these queries for monitoring and predicting influenza epidemics in South Korea. Our study was based on freely available weekly influenza incidence data and query data originating from the search engine on the Korean website Daum between April 3, 2011 and April 5, 2014. To select queries related to influenza epidemics, several approaches were applied: (1) exploring influenza-related words in social media data, (2) identifying the chief concerns related to influenza, and (3) using Web query recommendations. Optimal feature selection by least absolute shrinkage and selection operator (Lasso) and support vector machine for regression (SVR) were used to construct a model predicting influenza epidemics. In total, 146 queries related to influenza were generated through our initial query selection approach. A considerable proportion of optimal features for final models were derived from queries with reference to the social media data. The SVR model performed well: the prediction values were highly correlated with the recent observed influenza-like illness (r=.956; P<.001) and virological incidence rate (r=.963; P<.001). These results demonstrate the feasibility of using search queries to enhance influenza surveillance in South Korea. In addition, an approach for query selection using social media data seems ideal for supporting influenza surveillance based on search query data.

Estimating Influenza Outbreaks Using Both Search Engine Query Data and Social Media Data in South Korea

PubMed Central

Woo, Hyekyung; Shim, Eunyoung; Lee, Jong-Koo; Lee, Chang-Gun; Kim, Seong Hwan

2016-01-01

Background As suggested as early as in 2006, logs of queries submitted to search engines seeking information could be a source for detection of emerging influenza epidemics if changes in the volume of search queries are monitored (infodemiology). However, selecting queries that are most likely to be associated with influenza epidemics is a particular challenge when it comes to generating better predictions. Objective In this study, we describe a methodological extension for detecting influenza outbreaks using search query data; we provide a new approach for query selection through the exploration of contextual information gleaned from social media data. Additionally, we evaluate whether it is possible to use these queries for monitoring and predicting influenza epidemics in South Korea. Methods Our study was based on freely available weekly influenza incidence data and query data originating from the search engine on the Korean website Daum between April 3, 2011 and April 5, 2014. To select queries related to influenza epidemics, several approaches were applied: (1) exploring influenza-related words in social media data, (2) identifying the chief concerns related to influenza, and (3) using Web query recommendations. Optimal feature selection by least absolute shrinkage and selection operator (Lasso) and support vector machine for regression (SVR) were used to construct a model predicting influenza epidemics. Results In total, 146 queries related to influenza were generated through our initial query selection approach. A considerable proportion of optimal features for final models were derived from queries with reference to the social media data. The SVR model performed well: the prediction values were highly correlated with the recent observed influenza-like illness (r=.956; P<.001) and virological incidence rate (r=.963; P<.001). Conclusions These results demonstrate the feasibility of using search queries to enhance influenza surveillance in South Korea. In addition, an approach for query selection using social media data seems ideal for supporting influenza surveillance based on search query data. PMID:27377323

Algorithms for database-dependent search of MS/MS data.

PubMed

Matthiesen, Rune

2013-01-01

The frequent used bottom-up strategy for identification of proteins and their associated modifications generate nowadays typically thousands of MS/MS spectra that normally are matched automatically against a protein sequence database. Search engines that take as input MS/MS spectra and a protein sequence database are referred as database-dependent search engines. Many programs both commercial and freely available exist for database-dependent search of MS/MS spectra and most of the programs have excellent user documentation. The aim here is therefore to outline the algorithm strategy behind different search engines rather than providing software user manuals. The process of database-dependent search can be divided into search strategy, peptide scoring, protein scoring, and finally protein inference. Most efforts in the literature have been put in to comparing results from different software rather than discussing the underlining algorithms. Such practical comparisons can be cluttered by suboptimal implementation and the observed differences are frequently caused by software parameters settings which have not been set proper to allow even comparison. In other words an algorithmic idea can still be worth considering even if the software implementation has been demonstrated to be suboptimal. The aim in this chapter is therefore to split the algorithms for database-dependent searching of MS/MS data into the above steps so that the different algorithmic ideas become more transparent and comparable. Most search engines provide good implementations of the first three data analysis steps mentioned above, whereas the final step of protein inference are much less developed for most search engines and is in many cases performed by an external software. The final part of this chapter illustrates how protein inference is built into the VEMS search engine and discusses a stand-alone program SIR for protein inference that can import a Mascot search result.

`Googling' Terrorists: Are Northern Irish Terrorists Visible on Internet Search Engines?

NASA Astrophysics Data System (ADS)

Reilly, P.

In this chapter, the analysis suggests that Northern Irish terrorists are not visible on Web search engines when net users employ conventional Internet search techniques. Editors of mass media organisations traditionally have had the ability to decide whether a terrorist atrocity is `newsworthy,' controlling the `oxygen' supply that sustains all forms of terrorism. This process, also known as `gatekeeping,' is often influenced by the norms of social responsibility, or alternatively, with regard to the interests of the advertisers and corporate sponsors that sustain mass media organisations. The analysis presented in this chapter suggests that Internet search engines can also be characterised as `gatekeepers,' albeit without the ability to shape the content of Websites before it reaches net users. Instead, Internet search engines give priority retrieval to certain Websites within their directory, pointing net users towards these Websites rather than others on the Internet. Net users are more likely to click on links to the more `visible' Websites on Internet search engine directories, these sites invariably being the highest `ranked' in response to a particular search query. A number of factors including the design of the Website and the number of links to external sites determine the `visibility' of a Website on Internet search engines. The study suggests that Northern Irish terrorists and their sympathisers are unlikely to achieve a greater degree of `visibility' online than they enjoy in the conventional mass media through the perpetration of atrocities. Although these groups may have a greater degree of freedom on the Internet to publicise their ideologies, they are still likely to be speaking to the converted or members of the press. Although it is easier to locate Northern Irish terrorist organisations on Internet search engines by linking in via ideology, ideological description searches, such as `Irish Republican' and `Ulster Loyalist,' are more likely to generate links pointing towards the sites of research institutes and independent media organisations than sites sympathetic to Northern Irish terrorist organisations. The chapter argues that Northern Irish terrorists are only visible on search engines if net users select the correct search terms.

SciRide Finder: a citation-based paradigm in biomedical literature search.

PubMed

Volanakis, Adam; Krawczyk, Konrad

2018-04-18

There are more than 26 million peer-reviewed biomedical research items according to Medline/PubMed. This breadth of information is indicative of the progress in biomedical sciences on one hand, but an overload for scientists performing literature searches on the other. A major portion of scientific literature search is to find statements, numbers and protocols that can be cited to build an evidence-based narrative for a new manuscript. Because science builds on prior knowledge, such information has likely been written out and cited in an older manuscript. Thus, Cited Statements, pieces of text from scientific literature supported by citing other peer-reviewed publications, carry significant amount of condensed information on prior art. Based on this principle, we propose a literature search service, SciRide Finder (finder.sciride.org), which constrains the search corpus to such Cited Statements only. We demonstrate that Cited Statements can carry different information to this found in titles/abstracts and full text, giving access to alternative literature search results than traditional search engines. We further show how presenting search results as a list of Cited Statements allows researchers to easily find information to build an evidence-based narrative for their own manuscripts.

Surfing for suicide methods and help: content analysis of websites retrieved with search engines in Austria and the United States.

PubMed

Till, Benedikt; Niederkrotenthaler, Thomas

2014-08-01

The Internet provides a variety of resources for individuals searching for suicide-related information. Structured content-analytic approaches to assess intercultural differences in web contents retrieved with method-related and help-related searches are scarce. We used the 2 most popular search engines (Google and Yahoo/Bing) to retrieve US-American and Austrian search results for the term suicide, method-related search terms (e.g., suicide methods, how to kill yourself, painless suicide, how to hang yourself), and help-related terms (e.g., suicidal thoughts, suicide help) on February 11, 2013. In total, 396 websites retrieved with US search engines and 335 websites from Austrian searches were analyzed with content analysis on the basis of current media guidelines for suicide reporting. We assessed the quality of websites and compared findings across search terms and between the United States and Austria. In both countries, protective outweighed harmful website characteristics by approximately 2:1. Websites retrieved with method-related search terms (e.g., how to hang yourself) contained more harmful (United States: P < .001, Austria: P < .05) and fewer protective characteristics (United States: P < .001, Austria: P < .001) compared to the term suicide. Help-related search terms (e.g., suicidal thoughts) yielded more websites with protective characteristics (United States: P = .07, Austria: P < .01). Websites retrieved with U.S. search engines generally had more protective characteristics (P < .001) than searches with Austrian search engines. Resources with harmful characteristics were better ranked than those with protective characteristics (United States: P < .01, Austria: P < .05). The quality of suicide-related websites obtained depends on the search terms used. Preventive efforts to improve the ranking of preventive web content, particularly regarding method-related search terms, seem necessary. © Copyright 2014 Physicians Postgraduate Press, Inc.

What is the prevalence of health-related searches on the World Wide Web? Qualitative and quantitative analysis of search engine queries on the Internet

PubMed Central

Eysenbach, G.; Kohler, Ch.

2003-01-01

While health information is often said to be the most sought after information on the web, empirical data on the actual frequency of health-related searches on the web are missing. In the present study we aimed to determine the prevalence of health-related searches on the web by analyzing search terms entered by people into popular search engines. We also made some preliminary attempts in qualitatively describing and classifying these searches. Occasional difficulties in determining what constitutes a “health-related” search led us to propose and validate a simple method to automatically classify a search string as “health-related”. This method is based on determining the proportion of pages on the web containing the search string and the word “health”, as a proportion of the total number of pages with the search string alone. Using human codings as gold standard we plotted a ROC curve and determined empirically that if this “co-occurance rate” is larger than 35%, the search string can be said to be health-related (sensitivity: 85.2%, specificity 80.4%). The results of our “human” codings of search queries determined that about 4.5% of all searches are “health-related”. We estimate that globally a minimum of 6.75 Million health-related searches are being conducted on the web every day, which is roughly the same number of searches that have been conducted on the NLM Medlars system in 1996 in a full year. PMID:14728167

Taking It to the Top: A Lesson in Search Engine Optimization

ERIC Educational Resources Information Center

Frydenberg, Mark; Miko, John S.

2011-01-01

Search engine optimization (SEO), the promoting of a Web site so it achieves optimal position with a search engine's rankings, is an important strategy for organizations and individuals in order to promote their brands online. Techniques for achieving SEO are relevant to students of marketing, computing, media arts, and other disciplines, and many…

Enhanced identification of eligibility for depression research using an electronic medical record search engine.

PubMed

Seyfried, Lisa; Hanauer, David A; Nease, Donald; Albeiruti, Rashad; Kavanagh, Janet; Kales, Helen C

2009-12-01

Electronic medical records (EMRs) have become part of daily practice for many physicians. Attempts have been made to apply electronic search engine technology to speed EMR review. This was a prospective, observational study to compare the speed and clinical accuracy of a medical record search engine vs. manual review of the EMR. Three raters reviewed 49 cases in the EMR to screen for eligibility in a depression study using the electronic medical record search engine (EMERSE). One week later raters received a scrambled set of the same patients including 9 distractor cases, and used manual EMR review to determine eligibility. For both methods, accuracy was assessed for the original 49 cases by comparison with a gold standard rater. Use of EMERSE resulted in considerable time savings; chart reviews using EMERSE were significantly faster than traditional manual review (p=0.03). The percent agreement of raters with the gold standard (e.g. concurrent validity) using either EMERSE or manual review was not significantly different. Using a search engine optimized for finding clinical information in the free-text sections of the EMR can provide significant time savings while preserving clinical accuracy. The major power of this search engine is not from a more advanced and sophisticated search algorithm, but rather from a user interface designed explicitly to help users search the entire medical record in a way that protects health information.

Enhanced Identification of Eligibility for Depression Research Using an Electronic Medical Record Search Engine

PubMed Central

Seyfried, Lisa; Hanauer, David; Nease, Donald; Albeiruti, Rashad; Kavanagh, Janet; Kales, Helen C.

2009-01-01

Purpose Electronic medical records (EMR) have become part of daily practice for many physicians. Attempts have been made to apply electronic search engine technology to speed EMR review. This was a prospective, observational study to compare the speed and accuracy of electronic search engine vs. manual review of the EMR. Methods Three raters reviewed 49 cases in the EMR to screen for eligibility in a depression study using the electronic search engine (EMERSE). One week later raters received a scrambled set of the same patients including 9 distractor cases, and used manual EMR review to determine eligibility. For both methods, accuracy was assessed for the original 49 cases by comparison with a gold standard rater. Results Use of EMERSE resulted in considerable time savings; chart reviews using EMERSE were significantly faster than traditional manual review (p=0.03). The percent agreement of raters with the gold standard (e.g. concurrent validity) using either EMERSE or manual review was not significantly different. Conclusions Using a search engine optimized for finding clinical information in the free-text sections of the EMR can provide significant time savings while preserving reliability. The major power of this search engine is not from a more advanced and sophisticated search algorithm, but rather from a user interface designed explicitly to help users search the entire medical record in a way that protects health information. PMID:19560962

Adverse Reactions Associated With Cannabis Consumption as Evident From Search Engine Queries

PubMed Central

Lev-Ran, Shaul

2017-01-01

Background Cannabis is one of the most widely used psychoactive substances worldwide, but adverse drug reactions (ADRs) associated with its use are difficult to study because of its prohibited status in many countries. Objective Internet search engine queries have been used to investigate ADRs in pharmaceutical drugs. In this proof-of-concept study, we tested whether these queries can be used to detect the adverse reactions of cannabis use. Methods We analyzed anonymized queries from US-based users of Bing, a widely used search engine, made over a period of 6 months and compared the results with the prevalence of cannabis use as reported in the US National Survey on Drug Use in the Household (NSDUH) and with ADRs reported in the Food and Drug Administration’s Adverse Drug Reporting System. Predicted prevalence of cannabis use was estimated from the fraction of people making queries about cannabis, marijuana, and 121 additional synonyms. Predicted ADRs were estimated from queries containing layperson descriptions to 195 ICD-10 symptoms list. Results Our results indicated that the predicted prevalence of cannabis use at the US census regional level reaches an R2 of .71 NSDUH data. Queries for ADRs made by people who also searched for cannabis reveal many of the known adverse effects of cannabis (eg, cough and psychotic symptoms), as well as plausible unknown reactions (eg, pyrexia). Conclusions These results indicate that search engine queries can serve as an important tool for the study of adverse reactions of illicit drugs, which are difficult to study in other settings. PMID:29074469

Complex dynamics of our economic life on different scales: insights from search engine query data.

PubMed

Preis, Tobias; Reith, Daniel; Stanley, H Eugene

2010-12-28

Search engine query data deliver insight into the behaviour of individuals who are the smallest possible scale of our economic life. Individuals are submitting several hundred million search engine queries around the world each day. We study weekly search volume data for various search terms from 2004 to 2010 that are offered by the search engine Google for scientific use, providing information about our economic life on an aggregated collective level. We ask the question whether there is a link between search volume data and financial market fluctuations on a weekly time scale. Both collective 'swarm intelligence' of Internet users and the group of financial market participants can be regarded as a complex system of many interacting subunits that react quickly to external changes. We find clear evidence that weekly transaction volumes of S&P 500 companies are correlated with weekly search volume of corresponding company names. Furthermore, we apply a recently introduced method for quantifying complex correlations in time series with which we find a clear tendency that search volume time series and transaction volume time series show recurring patterns.

A geospatial search engine for discovering multi-format geospatial data across the web

Treesearch

Christopher Bone; Alan Ager; Ken Bunzel; Lauren Tierney

2014-01-01

The volume of publically available geospatial data on the web is rapidly increasing due to advances in server-based technologies and the ease at which data can now be created. However, challenges remain with connecting individuals searching for geospatial data with servers and websites where such data exist. The objective of this paper is to present a publically...

Generating Personalized Web Search Using Semantic Context

PubMed Central

Xu, Zheng; Chen, Hai-Yan; Yu, Jie

2015-01-01

The “one size fits the all” criticism of search engines is that when queries are submitted, the same results are returned to different users. In order to solve this problem, personalized search is proposed, since it can provide different search results based upon the preferences of users. However, existing methods concentrate more on the long-term and independent user profile, and thus reduce the effectiveness of personalized search. In this paper, the method captures the user context to provide accurate preferences of users for effectively personalized search. First, the short-term query context is generated to identify related concepts of the query. Second, the user context is generated based on the click through data of users. Finally, a forgetting factor is introduced to merge the independent user context in a user session, which maintains the evolution of user preferences. Experimental results fully confirm that our approach can successfully represent user context according to individual user information needs. PMID:26000335

Analyzing Medical Image Search Behavior: Semantics and Prediction of Query Results.

PubMed

De-Arteaga, Maria; Eggel, Ivan; Kahn, Charles E; Müller, Henning

2015-10-01

Log files of information retrieval systems that record user behavior have been used to improve the outcomes of retrieval systems, understand user behavior, and predict events. In this article, a log file of the ARRS GoldMiner search engine containing 222,005 consecutive queries is analyzed. Time stamps are available for each query, as well as masked IP addresses, which enables to identify queries from the same person. This article describes the ways in which physicians (or Internet searchers interested in medical images) search and proposes potential improvements by suggesting query modifications. For example, many queries contain only few terms and therefore are not specific; others contain spelling mistakes or non-medical terms that likely lead to poor or empty results. One of the goals of this report is to predict the number of results a query will have since such a model allows search engines to automatically propose query modifications in order to avoid result lists that are empty or too large. This prediction is made based on characteristics of the query terms themselves. Prediction of empty results has an accuracy above 88%, and thus can be used to automatically modify the query to avoid empty result sets for a user. The semantic analysis and data of reformulations done by users in the past can aid the development of better search systems, particularly to improve results for novice users. Therefore, this paper gives important ideas to better understand how people search and how to use this knowledge to improve the performance of specialized medical search engines.

Search engine as a diagnostic tool in difficult immunological and allergologic cases: is Google useful?

PubMed

Lombardi, C; Griffiths, E; McLeod, B; Caviglia, A; Penagos, M

2009-07-01

Web search engines are an important tool in communication and diffusion of knowledge. Among these, Google appears to be the most popular one: in August 2008, it accounted for 87% of all web searches in the UK, compared with Yahoo's 3.3%. Google's value as a diagnostic guide in general medicine was recently reported. The aim of this comparative cross-sectional study was to evaluate whether searching Google with disease-related terms was effective in the identification and diagnosis of complex immunological and allergic cases. Forty-five case reports were randomly selected by an independent observer from peer-reviewed medical journals. Clinical data were presented separately to three investigators, blinded to the final diagnoses. Investigator A was a Consultant with an expert knowledge in Internal Medicine and Allergy (IM&A) and basic computing skills. Investigator B was a Registrar in IM&A. Investigator C was a Research Nurse. Both Investigators B and C were familiar with computers and search engines. For every clinical case presented, each investigator independently carried out an Internet search using Google to provide a final diagnosis. Their results were then compared with the published diagnoses. Correct diagnoses were provided in 30/45 (66%) cases, 39/45 (86%) cases, and in 29/45 (64%) cases by investigator A, B, and C, respectively. All of the three investigators achieved the correct diagnosis in 19 cases (42%), and all of them failed in two cases. This Google-based search was useful to identify an appropriate diagnosis in complex immunological and allergic cases. Computing skills may help to get better results.

Anamneses-Based Internet Information Supply: Can a Combination of an Expert System and Meta-Search Engine Help Consumers find the Health Information they Require?

PubMed Central

Honekamp, Wilfried; Ostermann, Herwig

2010-01-01

An increasing number of people search for health information online. During the last 10 years various researchers have determined the requirements for an ideal consumer health information system. The aim of this study was to figure out, whether medical laymen can find a more accurate diagnosis for a given anamnesis via the developed prototype health information system than via ordinary internet search. In a randomized controlled trial, the prototype information system was evaluated by the assessment of two sample cases. Participants had to determine the diagnosis of a patient with a headache via information found searching the web. A patient’s history sheet and a computer with internet access were provided to the participants and they were guided through the study by an especially designed study website. The intervention group used the prototype information system; the control group used common search engines and portals. The numbers of correct diagnoses in each group were compared. A total of 140 (60/80) participants took part in two study sections. In the first case, which determined a common diagnosis, both groups did equally well. In the second section, which determined a less common and more complex case, the intervention group did significantly better (P=0.031) due to the tailored information supply. Using medical expert systems in combination with a portal searching meta-search engine represents a feasible strategy to provide reliable patient-tailored information and can ultimately contribute to patient safety with respect to information found via the internet. PMID:20502597

Turning the LHC ring into a new physics search machine

NASA Astrophysics Data System (ADS)

Orava, Risto

2017-03-01

The LHC Collider Ring is proposed to be turned into an ultimate automatic search engine for new physics in four consecutive phases: (1) Searches for heavy particles produced in Central Exclusive Process (CEP): pp → p + X + p based on the existing Beam Loss Monitoring (BLM) system of the LHC; (2) Feasibility study of using the LHC Ring as a gravitation wave antenna; (3) Extensions to the current BLM system to facilitate precise registration of the selected CEP proton exit points from the LHC beam vacuum chamber; (4) Integration of the BLM based event tagging system together with the trigger/data acquisition systems of the LHC experiments to facilitate an on-line automatic search machine for the physics of tomorrow.

Using a terminology server and consumer search phrases to help patients find physicians with particular expertise.

PubMed

Cole, Curtis L; Kanter, Andrew S; Cummens, Michael; Vostinar, Sean; Naeymi-Rad, Frank

2004-01-01

To design and implement a real world application using a terminology server to assist patients and physicians who use common language search terms to find specialist physicians with a particular clinical expertise. Terminology servers have been developed to help users encoding of information using complicated structured vocabulary during data entry tasks, such as recording clinical information. We describe a methodology using Personal Health Terminology trade mark and a SNOMED CT-based hierarchical concept server. Construction of a pilot mediated-search engine to assist users who use vernacular speech in querying data which is more technical than vernacular. This approach, which combines theoretical and practical requirements, provides a useful example of concept-based searching for physician referrals.

The Genetic-Algorithm-Based Normal Boundary Intersection (GANBI) Method; An Efficient Approach to Pareto Multiobjective Optimization for Engineering Design

DTIC Science & Technology

2006-05-15

alarm performance in a cost-effective manner is the use of track - before - detect strategies, in which multiple sensor detections must occur within the...corresponding to the traditional sensor coverage problem. Also, in the track - before - detect context, reference is made to the field-level functions of...detection and false alarm as successful search and false search, respectively, because the track - before - detect process serves as a searching function

Maximizing the sensitivity and reliability of peptide identification in large-scale proteomic experiments by harnessing multiple search engines.

PubMed

Yu, Wen; Taylor, J Alex; Davis, Michael T; Bonilla, Leo E; Lee, Kimberly A; Auger, Paul L; Farnsworth, Chris C; Welcher, Andrew A; Patterson, Scott D

2010-03-01

Despite recent advances in qualitative proteomics, the automatic identification of peptides with optimal sensitivity and accuracy remains a difficult goal. To address this deficiency, a novel algorithm, Multiple Search Engines, Normalization and Consensus is described. The method employs six search engines and a re-scoring engine to search MS/MS spectra against protein and decoy sequences. After the peptide hits from each engine are normalized to error rates estimated from the decoy hits, peptide assignments are then deduced using a minimum consensus model. These assignments are produced in a series of progressively relaxed false-discovery rates, thus enabling a comprehensive interpretation of the data set. Additionally, the estimated false-discovery rate was found to have good concordance with the observed false-positive rate calculated from known identities. Benchmarking against standard proteins data sets (ISBv1, sPRG2006) and their published analysis, demonstrated that the Multiple Search Engines, Normalization and Consensus algorithm consistently achieved significantly higher sensitivity in peptide identifications, which led to increased or more robust protein identifications in all data sets compared with prior methods. The sensitivity and the false-positive rate of peptide identification exhibit an inverse-proportional and linear relationship with the number of participating search engines.

Information Discovery and Retrieval Tools

DTIC Science & Technology

2004-12-01

information. This session will focus on the various Internet search engines , directories, and how to improve the user experience through the use of...such techniques as metadata, meta- search engines , subject specific search tools, and other developing technologies.

Information Discovery and Retrieval Tools

DTIC Science & Technology

2003-04-01

information. This session will focus on the various Internet search engines , directories, and how to improve the user experience through the use of...such techniques as metadata, meta- search engines , subject specific search tools, and other developing technologies.

Incorporating the Internet into Traditional Library Instruction.

ERIC Educational Resources Information Center

Fonseca, Tony; King, Monica

2000-01-01

Presents a template for teaching traditional library research and one for incorporating the Web. Highlights include the differences between directories and search engines; devising search strategies; creating search terms; how to choose search engines; evaluating online resources; helpful Web sites; and how to read URLs to evaluate a Web site's…

Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

NASA Astrophysics Data System (ADS)

Tong, S. S.

1986-01-01

The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

Aircraft gas-turbine engines: Noise reduction and vibration control. (Latest citations from Information Services in Mechanical Engineering data base). Published Search

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-06-01

The bibliography contains citations concerning the design and analysis of aircraft gas turbine engines with respect to noise and vibration control. Included are studies regarding the measurement and reduction of noise at its source, within the aircraft, and on the ground. Inlet, nozzle and core aerodynamic studies are cited. Propfan, turbofan, turboprop engines, and applications in short take-off and landing (STOL) aircraft are included. (Contains a minimum of 202 citations and includes a subject term index and title list.)

Data engineering systems: Computerized modeling and data bank capabilities for engineering analysis

NASA Technical Reports Server (NTRS)

Kopp, H.; Trettau, R.; Zolotar, B.

1984-01-01

The Data Engineering System (DES) is a computer-based system that organizes technical data and provides automated mechanisms for storage, retrieval, and engineering analysis. The DES combines the benefits of a structured data base system with automated links to large-scale analysis codes. While the DES provides the user with many of the capabilities of a computer-aided design (CAD) system, the systems are actually quite different in several respects. A typical CAD system emphasizes interactive graphics capabilities and organizes data in a manner that optimizes these graphics. On the other hand, the DES is a computer-aided engineering system intended for the engineer who must operationally understand an existing or planned design or who desires to carry out additional technical analysis based on a particular design. The DES emphasizes data retrieval in a form that not only provides the engineer access to search and display the data but also links the data automatically with the computer analysis codes.

PlateRunner: A Search Engine to Identify EMR Boilerplates.

PubMed

Divita, Guy; Workman, T Elizabeth; Carter, Marjorie E; Redd, Andrew; Samore, Matthew H; Gundlapalli, Adi V

2016-01-01

Medical text contains boilerplated content, an artifact of pull-down forms from EMRs. Boilerplated content is the source of challenges for concept extraction on clinical text. This paper introduces PlateRunner, a search engine on boilerplates from the US Department of Veterans Affairs (VA) EMR. Boilerplates containing concepts should be identified and reviewed to recognize challenging formats, identify high yield document titles, and fine tune section zoning. This search engine has the capability to filter negated and asserted concepts, save and search query results. This tool can save queries, search results, and documents found for later analysis.

What Major Search Engines Like Google, Yahoo and Bing Need to Know about Teachers in the UK?

ERIC Educational Resources Information Center

Seyedarabi, Faezeh

2014-01-01

This article briefly outlines the current major search engines' approach to teachers' web searching. The aim of this article is to make Web searching easier for teachers when searching for relevant online teaching materials, in general, and UK teacher practitioners at primary, secondary and post-compulsory levels, in particular. Therefore, major…

Brief Report: Consistency of Search Engine Rankings for Autism Websites

ERIC Educational Resources Information Center

Reichow, Brian; Naples, Adam; Steinhoff, Timothy; Halpern, Jason; Volkmar, Fred R.

2012-01-01

The World Wide Web is one of the most common methods used by parents to find information on autism spectrum disorders and most consumers find information through search engines such as Google or Bing. However, little is known about how the search engines operate or the consistency of the results that are returned over time. This study presents the…

D-score: a search engine independent MD-score.

PubMed

Vaudel, Marc; Breiter, Daniela; Beck, Florian; Rahnenführer, Jörg; Martens, Lennart; Zahedi, René P

2013-03-01

While peptides carrying PTMs are routinely identified in gel-free MS, the localization of the PTMs onto the peptide sequences remains challenging. Search engine scores of secondary peptide matches have been used in different approaches in order to infer the quality of site inference, by penalizing the localization whenever the search engine similarly scored two candidate peptides with different site assignments. In the present work, we show how the estimation of posterior error probabilities for peptide candidates allows the estimation of a PTM score called the D-score, for multiple search engine studies. We demonstrate the applicability of this score to three popular search engines: Mascot, OMSSA, and X!Tandem, and evaluate its performance using an already published high resolution data set of synthetic phosphopeptides. For those peptides with phosphorylation site inference uncertainty, the number of spectrum matches with correctly localized phosphorylation increased by up to 25.7% when compared to using Mascot alone, although the actual increase depended on the fragmentation method used. Since this method relies only on search engine scores, it can be readily applied to the scoring of the localization of virtually any modification at no additional experimental or in silico cost. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

How do Consumers Search for and Appraise Information on Medicines on the Internet? A Qualitative Study Using Focus Groups

PubMed Central

Aslani, Parisa; Williams, Kylie A

2003-01-01

Background Many consumers use the Internet to find information about their medicines. It is widely acknowledged that health information on the Internet is of variable quality and therefore the search and appraisal skills of consumers are important for selecting and assessing this information. The way consumers choose and evaluate information on medicines on the Internet is important because it has been shown that written information on medicines can influence consumer attitudes to and use of medicines. Objective To explore consumer experiences in searching for and appraising Internet-based information on medicines. Methods Six focus groups (N = 46 participants) were conducted in metropolitan Sydney, Australia from March to May 2003 with consumers who had used the Internet for information on medicines. Verbatim transcripts of the group discussions were analyzed using a grounded theory approach. Results All participants reported using a search engine to find information on medicines. Choice of search engine was determined by factors such as the workplace or educational environments, or suggestions by family or friends. Some participants found information solely by typing the medicine name (drug or brand name) into the search engine, while others searched using broader terms. Search skills ranged widely from more-advanced (using quotation marks and phrases) to less-than-optimal (such as typing in questions and full sentences). Many participants selected information from the first page of search results by looking for keywords and descriptions in the search results, and by looking for the source of the information as apparent in the URL. Opinions on credible sources of information on medicines varied with some participants regarding information by pharmaceutical companies as the "official" information on a medicine, and others preferring what they considered to be impartial sources such as governments, organizations, and educational institutions. It was clear that although most participants were skeptical of trusting information on the Internet, they had not paid conscious attention to how they selected information on medicines. Despite this, it was evident that participants viewed the Internet as an important source for information on medicines. Conclusions The results showed that there was a range of search and appraisal skills among participants, with many reporting a limited awareness of how they found and evaluated Internet-based information on medicines. Poor interpretation of written information on medicines has been shown to lead to anxiety and poor compliance to therapy. This issue is more important for Internet-based information since it is not subject to quality control and standardization as is written information on medicines. Therefore, there is a need for promoting consumer search and appraisal skills when using this information. Educating consumers in how to find and interpret Internet-based information on medicines may help them use their medicines in a safer and more-effective way. PMID:14713661

MedlinePlus Connect: Web Application

MedlinePlus

... will result in a query to the MedlinePlus search engine. If you specify a code and the name/ ... system or problem code, will use the MedlinePlus search engine (English only): https://connect.medlineplus.gov/application?mainSearchCriteria. ...

Real-time earthquake monitoring using a search engine method.

PubMed

Zhang, Jie; Zhang, Haijiang; Chen, Enhong; Zheng, Yi; Kuang, Wenhuan; Zhang, Xiong

2014-12-04

When an earthquake occurs, seismologists want to use recorded seismograms to infer its location, magnitude and source-focal mechanism as quickly as possible. If such information could be determined immediately, timely evacuations and emergency actions could be undertaken to mitigate earthquake damage. Current advanced methods can report the initial location and magnitude of an earthquake within a few seconds, but estimating the source-focal mechanism may require minutes to hours. Here we present an earthquake search engine, similar to a web search engine, that we developed by applying a computer fast search method to a large seismogram database to find waveforms that best fit the input data. Our method is several thousand times faster than an exact search. For an Mw 5.9 earthquake on 8 March 2012 in Xinjiang, China, the search engine can infer the earthquake's parameters in <1 s after receiving the long-period surface wave data.

Real-time earthquake monitoring using a search engine method

PubMed Central

Zhang, Jie; Zhang, Haijiang; Chen, Enhong; Zheng, Yi; Kuang, Wenhuan; Zhang, Xiong

2014-01-01

When an earthquake occurs, seismologists want to use recorded seismograms to infer its location, magnitude and source-focal mechanism as quickly as possible. If such information could be determined immediately, timely evacuations and emergency actions could be undertaken to mitigate earthquake damage. Current advanced methods can report the initial location and magnitude of an earthquake within a few seconds, but estimating the source-focal mechanism may require minutes to hours. Here we present an earthquake search engine, similar to a web search engine, that we developed by applying a computer fast search method to a large seismogram database to find waveforms that best fit the input data. Our method is several thousand times faster than an exact search. For an Mw 5.9 earthquake on 8 March 2012 in Xinjiang, China, the search engine can infer the earthquake’s parameters in <1 s after receiving the long-period surface wave data. PMID:25472861

Just-in-Time Web Searches for Trainers & Adult Educators.

ERIC Educational Resources Information Center

Kirk, James J.

Trainers and adult educators often need to quickly locate quality information on the World Wide Web (WWW) and need assistance in searching for such information. A "search engine" is an application used to query existing information on the WWW. The three types of search engines are computer-generated indexes, directories, and meta search…

Discovering How Students Search a Library Web Site: A Usability Case Study.

ERIC Educational Resources Information Center

Augustine, Susan; Greene, Courtney

2002-01-01

Discusses results of a usability study at the University of Illinois Chicago that investigated whether Internet search engines have influenced the way students search library Web sites. Results show students use the Web site's internal search engine rather than navigating through the pages; have difficulty interpreting library terminology; and…

Use of an Academic Library Web Site Search Engine.

ERIC Educational Resources Information Center

Fagan, Jody Condit

2002-01-01

Describes an analysis of the search engine logs of Southern Illinois University, Carbondale's library to determine how patrons used the site search. Discusses results that showed patrons did not understand the function of the search and explains improvements that were made in the Web site and in online reference services. (Author/LRW)

A Real-Time All-Atom Structural Search Engine for Proteins

PubMed Central

Gonzalez, Gabriel; Hannigan, Brett; DeGrado, William F.

2014-01-01

Protein designers use a wide variety of software tools for de novo design, yet their repertoire still lacks a fast and interactive all-atom search engine. To solve this, we have built the Suns program: a real-time, atomic search engine integrated into the PyMOL molecular visualization system. Users build atomic-level structural search queries within PyMOL and receive a stream of search results aligned to their query within a few seconds. This instant feedback cycle enables a new “designability”-inspired approach to protein design where the designer searches for and interactively incorporates native-like fragments from proven protein structures. We demonstrate the use of Suns to interactively build protein motifs, tertiary interactions, and to identify scaffolds compatible with hot-spot residues. The official web site and installer are located at http://www.degradolab.org/suns/ and the source code is hosted at https://github.com/godotgildor/Suns (PyMOL plugin, BSD license), https://github.com/Gabriel439/suns-cmd (command line client, BSD license), and https://github.com/Gabriel439/suns-search (search engine server, GPLv2 license). PMID:25079944

A real-time all-atom structural search engine for proteins.

PubMed

Gonzalez, Gabriel; Hannigan, Brett; DeGrado, William F

2014-07-01

Protein designers use a wide variety of software tools for de novo design, yet their repertoire still lacks a fast and interactive all-atom search engine. To solve this, we have built the Suns program: a real-time, atomic search engine integrated into the PyMOL molecular visualization system. Users build atomic-level structural search queries within PyMOL and receive a stream of search results aligned to their query within a few seconds. This instant feedback cycle enables a new "designability"-inspired approach to protein design where the designer searches for and interactively incorporates native-like fragments from proven protein structures. We demonstrate the use of Suns to interactively build protein motifs, tertiary interactions, and to identify scaffolds compatible with hot-spot residues. The official web site and installer are located at http://www.degradolab.org/suns/ and the source code is hosted at https://github.com/godotgildor/Suns (PyMOL plugin, BSD license), https://github.com/Gabriel439/suns-cmd (command line client, BSD license), and https://github.com/Gabriel439/suns-search (search engine server, GPLv2 license).

IdentiPy: An Extensible Search Engine for Protein Identification in Shotgun Proteomics.

PubMed

Levitsky, Lev I; Ivanov, Mark V; Lobas, Anna A; Bubis, Julia A; Tarasova, Irina A; Solovyeva, Elizaveta M; Pridatchenko, Marina L; Gorshkov, Mikhail V

2018-06-18

We present an open-source, extensible search engine for shotgun proteomics. Implemented in Python programming language, IdentiPy shows competitive processing speed and sensitivity compared with the state-of-the-art search engines. It is equipped with a user-friendly web interface, IdentiPy Server, enabling the use of a single server installation accessed from multiple workstations. Using a simplified version of X!Tandem scoring algorithm and its novel "autotune" feature, IdentiPy outperforms the popular alternatives on high-resolution data sets. Autotune adjusts the search parameters for the particular data set, resulting in improved search efficiency and simplifying the user experience. IdentiPy with the autotune feature shows higher sensitivity compared with the evaluated search engines. IdentiPy Server has built-in postprocessing and protein inference procedures and provides graphic visualization of the statistical properties of the data set and the search results. It is open-source and can be freely extended to use third-party scoring functions or processing algorithms and allows customization of the search workflow for specialized applications.

Mobile medical visual information retrieval.

PubMed

Depeursinge, Adrien; Duc, Samuel; Eggel, Ivan; Müller, Henning

2012-01-01

In this paper, we propose mobile access to peer-reviewed medical information based on textual search and content-based visual image retrieval. Web-based interfaces designed for limited screen space were developed to query via web services a medical information retrieval engine optimizing the amount of data to be transferred in wireless form. Visual and textual retrieval engines with state-of-the-art performance were integrated. Results obtained show a good usability of the software. Future use in clinical environments has the potential of increasing quality of patient care through bedside access to the medical literature in context.

Integration of Language and Cognition at Pre-Conceptual Level

DTIC Science & Technology

2003-10-04

and cognition at a pre-conceptual level, where conceptual and emotional contents are not differentiated might be interesting for theoretical linguistics and for practical development of understanding-based search engines .

Preliminary Comparison of Three Search Engines for Point of Care Access to MEDLINE® Citations

PubMed Central

Hauser, Susan E.; Demner-Fushman, Dina; Ford, Glenn M.; Jacobs, Joshua L.; Thoma, George

2006-01-01

Medical resident physicians used MD on Tap in real time to search for MEDLINE citations relevant to clinical questions using three search engines: Essie, Entrez and Google™, in order of performance. PMID:17238564

Index Compression and Efficient Query Processing in Large Web Search Engines

ERIC Educational Resources Information Center

Ding, Shuai

2013-01-01

The inverted index is the main data structure used by all the major search engines. Search engines build an inverted index on their collection to speed up query processing. As the size of the web grows, the length of the inverted list structures, which can easily grow to hundreds of MBs or even GBs for common terms (roughly linear in the size of…

Electronic Document Management Using Inverted Files System

NASA Astrophysics Data System (ADS)

Suhartono, Derwin; Setiawan, Erwin; Irwanto, Djon

2014-03-01

The amount of documents increases so fast. Those documents exist not only in a paper based but also in an electronic based. It can be seen from the data sample taken by the SpringerLink publisher in 2010, which showed an increase in the number of digital document collections from 2003 to mid of 2010. Then, how to manage them well becomes an important need. This paper describes a new method in managing documents called as inverted files system. Related with the electronic based document, the inverted files system will closely used in term of its usage to document so that it can be searched over the Internet using the Search Engine. It can improve document search mechanism and document save mechanism.

Raising the IQ in full-text searching via intelligent querying

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kero, R.; Russell, L.; Swietlik, C.

1994-11-01

Current Information Retrieval (IR) technologies allow for efficient access to relevant information, provided that user selected query terms coincide with the specific linguistical choices made by the authors whose works constitute the text-base. Therefore, the challenge is to enhance the limited searching capability of state-of-the-practice IR. This can be done either with augmented clients that overcome current server searching deficiencies, or with added capabilities that can augment searching algorithms on the servers. The technology being investigated is that of deductive databases, with a set of new techniques called cooperative answering. This technology utilizes semantic networks to allow for navigation betweenmore » possible query search term alternatives. The augmented search terms are passed to an IR engine and the results can be compared. The project utilizes the OSTI Environment, Safety and Health Thesaurus to populate the domain specific semantic network and the text base of ES&H related documents from the Facility Profile Information Management System as the domain specific search space.« less

LIVIVO - the Vertical Search Engine for Life Sciences.

PubMed

Müller, Bernd; Poley, Christoph; Pössel, Jana; Hagelstein, Alexandra; Gübitz, Thomas

2017-01-01

The explosive growth of literature and data in the life sciences challenges researchers to keep track of current advancements in their disciplines. Novel approaches in the life science like the One Health paradigm require integrated methodologies in order to link and connect heterogeneous information from databases and literature resources. Current publications in the life sciences are increasingly characterized by the employment of trans-disciplinary methodologies comprising molecular and cell biology, genetics, genomic, epigenomic, transcriptional and proteomic high throughput technologies with data from humans, plants, and animals. The literature search engine LIVIVO empowers retrieval functionality by incorporating various literature resources from medicine, health, environment, agriculture and nutrition. LIVIVO is developed in-house by ZB MED - Information Centre for Life Sciences. It provides a user-friendly and usability-tested search interface with a corpus of 55 Million citations derived from 50 databases. Standardized application programming interfaces are available for data export and high throughput retrieval. The search functions allow for semantic retrieval with filtering options based on life science entities. The service oriented architecture of LIVIVO uses four different implementation layers to deliver search services. A Knowledge Environment is developed by ZB MED to deal with the heterogeneity of data as an integrative approach to model, store, and link semantic concepts within literature resources and databases. Future work will focus on the exploitation of life science ontologies and on the employment of NLP technologies in order to improve query expansion, filters in faceted search, and concept based relevancy rankings in LIVIVO.

Automated Data Tagging in the HLA

NASA Astrophysics Data System (ADS)

Gaffney, N. I.; Miller, W. W.

2008-08-01

One of the more powerful and popular forms of data organization implemented in most popular information sharing web applications is data tagging. With a rich user base from which to gather and digest tags, many interesting and often unanticipated yet very useful associations are revealed. With regard to an existing information, the astronomical community has a rich pool of existing digitally stored and searchable data than any of the currently popular web community, such as You Tube or My Space, had when they started. In initial experiments with the search engine for the Hubble Legacy Archive, we have created a simple yet powerful scheme by which the information from a footprint service, the NED and SIMBAD catalog services, and the ADS abstracts and keywords can be used to initially tag data with standard keywords. By then ingesting this into a public ally available information search engine, such as Apache Lucene, one can create a simple and powerful data tag search engine and association system. By then augmenting this with user provided keys and usage pattern analysis, one can produce a powerful modern data mining system for any astronomical data warehouse.

Google Trends: Ready for real-time suicide prevention or just a Zeta-Jones effect? An exploratory study.

PubMed

Fond, Guillaume; Gaman, Alexandru; Brunel, Lore; Haffen, Emmanuel; Llorca, Pierre-Michel

2015-08-30

Two studies have shown that increasing the consultation of the word "suicide" in the Google search engine was associated with a subsequent increase in the prevalence of suicide attempts. The main goal of this article was to explore the trends generated by a key-word search associated with suicide, depression and bipolarity in an attempt to identify general trends (disorders epidemics in the population/"real events" vs newsworthy advertisement/"media event"). Based on previous studies, the frequency of the search words "how to suicide" and "commit suicide" were analyzed for suicide, as well as "depression" (for depressive disorders) and "bipolar disorder". Together, these analyses suggest that the search for the words "how to suicide" or "commit suicide" on the Google search engine may be a good indicator for suicide prevention policies. However, the tool is not developed enough to date to be used as a real time dynamic indicator of suicide epidemics. The frequency of the search for the word "suicide" was associated with those for "depression" but not for "bipolar disorder", but searches for psychiatric conditions seem to be influenced by media events more than by real events in the general population. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Identification of volatile and semivolatile compounds in chemical ionization GC-MS using a mass-to-structure (MTS) Search Engine with integral isotope pattern ranking.

PubMed

Liao, Wenta; Draper, William M

2013-02-21

The mass-to-structure or MTS Search Engine is an Access 2010 database containing theoretical molecular mass information for 19,438 compounds assembled from common sources such as the Merck Index, pesticide and pharmaceutical compilations, and chemical catalogues. This database, which contains no experimental mass spectral data, was developed as an aid to identification of compounds in atmospheric pressure ionization (API)-LC-MS. This paper describes a powerful upgrade to this database, a fully integrated utility for filtering or ranking candidates based on isotope ratios and patterns. The new MTS Search Engine is applied here to the identification of volatile and semivolatile compounds including pesticides, nitrosoamines and other pollutants. Methane and isobutane chemical ionization (CI) GC-MS spectra were obtained from unit mass resolution mass spectrometers to determine MH(+) masses and isotope ratios. Isotopes were measured accurately with errors of <4% and <6%, respectively, for A + 1 and A + 2 peaks. Deconvolution of interfering isotope clusters (e.g., M(+) and [M - H](+)) was required for accurate determination of the A + 1 isotope in halogenated compounds. Integrating the isotope data greatly improved the speed and accuracy of the database identifications. The database accurately identified unknowns from isobutane CI spectra in 100% of cases where as many as 40 candidates satisfied the mass tolerance. The paper describes the development and basic operation of the new MTS Search Engine and details performance testing with over 50 model compounds.

Characteristics of public concern on haze in China and its relationship with air quality in urban areas.

PubMed

Lu, Yaling; Wang, Yuan; Zuo, Jian; Jiang, Hongqiang; Huang, Dacang; Rameezdeen, Raufdeen

2018-10-01

Severe air pollution associated with the rapid urbanization is a pressing issue in China. Moreover, the public awareness of environmental protection in China is awakening, which poses enormous pressure on governments to enforce environmental regulations. The study of environmental problems from the public perspective plays a crucial role in effective environmental governance. The Baidu search engine is the China's largest search engine. The search index of haze based on Baidu search engine reflects the public concern on air quality in China. The aim of this study is to uncover important relationships between public concern and air quality monitoring data based on the case study of haze pollution crisis in China. The results indicate that: (1) the year 2013 is the turning point of the public concern on air quality in China; (2) according to daily data analysis, the search index of haze has increased progressively with increased PM 2.5 concentration with a time lag of 0-4 days and the lag time has a declining tendency from 2013 to 2017; (3) according to annual data analysis, the public concern showed a weak correlation with air quality and they showed an opposite temporal trend. However, when the long-term annual trend was removed, the strong positive correlation emerges between the fluctuation parts of the search index of haze and monitoring data of air quality. This indicates the public is more sensitive to the short-term fluctuation of air quality. The results of this paper provide statistical evidence on the evolution of public concern on air quality from 2013 to 2017. This study will help policy makers to better understand the patterns of the public's perception of environmental problems and consequently improve the government's capability to deal with these challenges. Copyright © 2018 Elsevier B.V. All rights reserved.

Can electronic search engines optimize screening of search results in systematic reviews: an empirical study.

PubMed

Sampson, Margaret; Barrowman, Nicholas J; Moher, David; Clifford, Tammy J; Platt, Robert W; Morrison, Andra; Klassen, Terry P; Zhang, Li

2006-02-24

Most electronic search efforts directed at identifying primary studies for inclusion in systematic reviews rely on the optimal Boolean search features of search interfaces such as DIALOG and Ovid. Our objective is to test the ability of an Ultraseek search engine to rank MEDLINE records of the included studies of Cochrane reviews within the top half of all the records retrieved by the Boolean MEDLINE search used by the reviewers. Collections were created using the MEDLINE bibliographic records of included and excluded studies listed in the review and all records retrieved by the MEDLINE search. Records were converted to individual HTML files. Collections of records were indexed and searched through a statistical search engine, Ultraseek, using review-specific search terms. Our data sources, systematic reviews published in the Cochrane library, were included if they reported using at least one phase of the Cochrane Highly Sensitive Search Strategy (HSSS), provided citations for both included and excluded studies and conducted a meta-analysis using a binary outcome measure. Reviews were selected if they yielded between 1000-6000 records when the MEDLINE search strategy was replicated. Nine Cochrane reviews were included. Included studies within the Cochrane reviews were found within the first 500 retrieved studies more often than would be expected by chance. Across all reviews, recall of included studies into the top 500 was 0.70. There was no statistically significant difference in ranking when comparing included studies with just the subset of excluded studies listed as excluded in the published review. The relevance ranking provided by the search engine was better than expected by chance and shows promise for the preliminary evaluation of large results from Boolean searches. A statistical search engine does not appear to be able to make fine discriminations concerning the relevance of bibliographic records that have been pre-screened by systematic reviewers.

Modeling Group Interactions via Open Data Sources

DTIC Science & Technology

2011-08-30

data. The state-of-art search engines are designed to help general query-specific search and not suitable for finding disconnected online groups. The...groups, (2) developing innovative mathematical and statistical models and efficient algorithms that leverage existing search engines and employ

Systematic harmonic power laws inter-relating multiple fundamental constants

NASA Astrophysics Data System (ADS)

Chakeres, Donald; Buckhanan, Wayne; Andrianarijaona, Vola

2017-01-01

Power laws and harmonic systems are ubiquitous in physics. We hypothesize that 2, π, the electron, Bohr radius, Rydberg constant, neutron, fine structure constant, Higgs boson, top quark, kaons, pions, muon, Tau, W, and Z when scaled in a common single unit are all inter-related by systematic harmonic powers laws. This implies that if the power law is known it is possible to derive a fundamental constant's scale in the absence of any direct experimental data of that constant. This is true for the case of the hydrogen constants. We created a power law search engine computer program that randomly generated possible positive or negative powers searching when the product of logical groups of constants equals 1, confirming they are physically valid. For 2, π, and the hydrogen constants the search engine found Planck's constant, Coulomb's energy law, and the kinetic energy law. The product of ratios defined by two constants each was the standard general format. The search engine found systematic resonant power laws based on partial harmonic fraction powers of the neutron for all of the constants with products near 1, within their known experimental precision, when utilized with appropriate hydrogen constants. We conclude that multiple fundamental constants are inter-related within a harmonic power law system.

Committee on Women in Science, Engineering, and Medicine (CWSEM)

Science.gov Websites

Skip to Main Content Contact Us | Search: Search The National Academies of Sciences, Engineering and Medicine Committee on Women in Science, Engineering, and Medicine Committee on Women in Science , Engineering, and Medicine Policy and Global Affairs Home About Us Members Subscribe to CWSEM Alerts Resources

Reconsidering the Rhizome: A Textual Analysis of Web Search Engines as Gatekeepers of the Internet

NASA Astrophysics Data System (ADS)

Hess, A.

Critical theorists have often drawn from Deleuze and Guattari's notion of the rhizome when discussing the potential of the Internet. While the Internet may structurally appear as a rhizome, its day-to-day usage by millions via search engines precludes experiencing the random interconnectedness and potential democratizing function. Through a textual analysis of four search engines, I argue that Web searching has grown hierarchies, or "trees," that organize data in tracts of knowledge and place users in marketing niches rather than assist in the development of new knowledge.

E-Referencer: Transforming Boolean OPACs to Web Search Engines.

ERIC Educational Resources Information Center

Khoo, Christopher S. G.; Poo, Danny C. C.; Toh, Teck-Kang; Hong, Glenn

E-Referencer is an expert intermediary system for searching library online public access catalogs (OPACs) on the World Wide Web. It is implemented as a proxy server that mediates the interaction between the user and Boolean OPACs. It transforms a Boolean OPAC into a retrieval system with many of the search capabilities of Web search engines.…

The Effect of Individual Differences on Searching the Web.

ERIC Educational Resources Information Center

Ihadjadene, Madjid; Chaudiron, Stephanne,; Martins, Daniel

2003-01-01

Reports results from a project that investigated the influence of two types of expertise--knowledge of the search domain and experience of the Web search engines--on students' use of a Web search engine. Results showed participants with good knowledge in the domain and participants with high experience of the Web had the best performances. (AEF)

Document Clustering Approach for Meta Search Engine

NASA Astrophysics Data System (ADS)

Kumar, Naresh, Dr.

2017-08-01

The size of WWW is growing exponentially with ever change in technology. This results in huge amount of information with long list of URLs. Manually it is not possible to visit each page individually. So, if the page ranking algorithms are used properly then user search space can be restricted up to some pages of searched results. But available literatures show that no single search system can provide qualitative results from all the domains. This paper provides solution to this problem by introducing a new meta search engine that determine the relevancy of query corresponding to web page and cluster the results accordingly. The proposed approach reduces the user efforts, improves the quality of results and performance of the meta search engine.

Adverse Reactions Associated With Cannabis Consumption as Evident From Search Engine Queries.

PubMed

Yom-Tov, Elad; Lev-Ran, Shaul

2017-10-26

Cannabis is one of the most widely used psychoactive substances worldwide, but adverse drug reactions (ADRs) associated with its use are difficult to study because of its prohibited status in many countries. Internet search engine queries have been used to investigate ADRs in pharmaceutical drugs. In this proof-of-concept study, we tested whether these queries can be used to detect the adverse reactions of cannabis use. We analyzed anonymized queries from US-based users of Bing, a widely used search engine, made over a period of 6 months and compared the results with the prevalence of cannabis use as reported in the US National Survey on Drug Use in the Household (NSDUH) and with ADRs reported in the Food and Drug Administration's Adverse Drug Reporting System. Predicted prevalence of cannabis use was estimated from the fraction of people making queries about cannabis, marijuana, and 121 additional synonyms. Predicted ADRs were estimated from queries containing layperson descriptions to 195 ICD-10 symptoms list. Our results indicated that the predicted prevalence of cannabis use at the US census regional level reaches an R 2 of .71 NSDUH data. Queries for ADRs made by people who also searched for cannabis reveal many of the known adverse effects of cannabis (eg, cough and psychotic symptoms), as well as plausible unknown reactions (eg, pyrexia). These results indicate that search engine queries can serve as an important tool for the study of adverse reactions of illicit drugs, which are difficult to study in other settings. ©Elad Yom-Tov, Shaul Lev-Ran. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 26.10.2017.

Collaborative search in electronic health records.

PubMed

Zheng, Kai; Mei, Qiaozhu; Hanauer, David A

2011-05-01

A full-text search engine can be a useful tool for augmenting the reuse value of unstructured narrative data stored in electronic health records (EHR). A prominent barrier to the effective utilization of such tools originates from users' lack of search expertise and/or medical-domain knowledge. To mitigate the issue, the authors experimented with a 'collaborative search' feature through a homegrown EHR search engine that allows users to preserve their search knowledge and share it with others. This feature was inspired by the success of many social information-foraging techniques used on the web that leverage users' collective wisdom to improve the quality and efficiency of information retrieval. The authors conducted an empirical evaluation study over a 4-year period. The user sample consisted of 451 academic researchers, medical practitioners, and hospital administrators. The data were analyzed using a social-network analysis to delineate the structure of the user collaboration networks that mediated the diffusion of knowledge of search. The users embraced the concept with considerable enthusiasm. About half of the EHR searches processed by the system (0.44 million) were based on stored search knowledge; 0.16 million utilized shared knowledge made available by other users. The social-network analysis results also suggest that the user-collaboration networks engendered by the collaborative search feature played an instrumental role in enabling the transfer of search knowledge across people and domains. Applying collaborative search, a social information-foraging technique popularly used on the web, may provide the potential to improve the quality and efficiency of information retrieval in healthcare.

Caught on the Web

ERIC Educational Resources Information Center

Isakson, Carol

2004-01-01

Search engines rapidly add new services and experimental tools in trying to outmaneuver each other for customers. In this article, the author describes the latest additional services of some search engines and provides its sources. The author also suggests tips for using these new search upgrades.

Towards iconic language for patient records, drug monographs, guidelines and medical search engines.

PubMed

Lamy, Jean-Baptiste; Duclos, Catherine; Hamek, Saliha; Beuscart-Zéphir, Marie-Catherine; Kerdelhué, Gaetan; Darmoni, Stefan; Favre, Madeleine; Falcoff, Hector; Simon, Christian; Pereira, Suzanne; Serrot, Elisabeth; Mitouard, Thierry; Hardouin, Etienne; Kergosien, Yannick; Venot, Alain

2010-01-01

Practicing physicians have limited time for consulting medical knowledge and records. We have previously shown that using icons instead of text to present drug monographs may allow contraindications and adverse effects to be identified more rapidly and more accurately. These findings were based on the use of an iconic language designed for drug knowledge, providing icons for many medical concepts, including diseases, antecedents, drug classes and tests. In this paper, we describe a new project aimed at extending this iconic language, and exploring the possible applications of these icons in medicine. Based on evaluators' comments, focus groups of physicians and opinions of academic, industrial and associative partners, we propose iconic applications related to patient records, for example summarizing patient conditions, searching for specific clinical documents and helping to code structured data. Other applications involve the presentation of clinical practice guidelines and improving the interface of medical search engines. These new applications could use the same iconic language that was designed for drug knowledge, with a few additional items that respect the logic of the language.

Semantics-Based Intelligent Indexing and Retrieval of Digital Images - A Case Study

NASA Astrophysics Data System (ADS)

Osman, Taha; Thakker, Dhavalkumar; Schaefer, Gerald

The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they typically rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this chapter we present a semantically enabled image annotation and retrieval engine that is designed to satisfy the requirements of commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as presenting our initial thoughts on exploiting lexical databases for explicit semantic-based query expansion.

Quality of Web-Based Information on Cannabis Addiction

ERIC Educational Resources Information Center

Khazaal, Yasser; Chatton, Anne; Cochand, Sophie; Zullino, Daniele

2008-01-01

This study evaluated the quality of Web-based information on cannabis use and addiction and investigated particular content quality indicators. Three keywords ("cannabis addiction," "cannabis dependence," and "cannabis abuse") were entered into two popular World Wide Web search engines. Websites were assessed with a standardized proforma designed…

Merging the Internet and Hypermedia in the English Language Arts.

ERIC Educational Resources Information Center

Reed, W. Michael; Wells, John G.

1997-01-01

Discussion of hypermedia and computer-mediated communication focuses on a project that merges a language arts Internet resource with a hypermedia-based knowledge construction approach to learning. Highlights include constructing a HyperCard-based program on Shakespeare's "Hamlet," gophers and search engines, downloading, collaborative…

MEGGASENSE - The Metagenome/Genome Annotated Sequence Natural Language Search Engine: A Platform for 
the Construction of Sequence Data Warehouses.

PubMed

Gacesa, Ranko; Zucko, Jurica; Petursdottir, Solveig K; Gudmundsdottir, Elisabet Eik; Fridjonsson, Olafur H; Diminic, Janko; Long, Paul F; Cullum, John; Hranueli, Daslav; Hreggvidsson, Gudmundur O; Starcevic, Antonio

2017-06-01

The MEGGASENSE platform constructs relational databases of DNA or protein sequences. The default functional analysis uses 14 106 hidden Markov model (HMM) profiles based on sequences in the KEGG database. The Solr search engine allows sophisticated queries and a BLAST search function is also incorporated. These standard capabilities were used to generate the SCATT database from the predicted proteome of Streptomyces cattleya . The implementation of a specialised metagenome database (AMYLOMICS) for bioprospecting of carbohydrate-modifying enzymes is described. In addition to standard assembly of reads, a novel 'functional' assembly was developed, in which screening of reads with the HMM profiles occurs before the assembly. The AMYLOMICS database incorporates additional HMM profiles for carbohydrate-modifying enzymes and it is illustrated how the combination of HMM and BLAST analyses helps identify interesting genes. A variety of different proteome and metagenome databases have been generated by MEGGASENSE.

Sundanese ancient manuscripts search engine using probability approach

NASA Astrophysics Data System (ADS)

Suryani, Mira; Hadi, Setiawan; Paulus, Erick; Nurma Yulita, Intan; Supriatna, Asep K.

2017-10-01

Today, Information and Communication Technology (ICT) has become a regular thing for every aspect of live include cultural and heritage aspect. Sundanese ancient manuscripts as Sundanese heritage are in damage condition and also the information that containing on it. So in order to preserve the information in Sundanese ancient manuscripts and make them easier to search, a search engine has been developed. The search engine must has good computing ability. In order to get the best computation in developed search engine, three types of probabilistic approaches: Bayesian Networks Model, Divergence from Randomness with PL2 distribution, and DFR-PL2F as derivative form DFR-PL2 have been compared in this study. The three probabilistic approaches supported by index of documents and three different weighting methods: term occurrence, term frequency, and TF-IDF. The experiment involved 12 Sundanese ancient manuscripts. From 12 manuscripts there are 474 distinct terms. The developed search engine tested by 50 random queries for three types of query. The experiment results showed that for the single query and multiple query, the best searching performance given by the combination of PL2F approach and TF-IDF weighting method. The performance has been evaluated using average time responds with value about 0.08 second and Mean Average Precision (MAP) about 0.33.

"There is nothing like looking, if you want to find something" - asking questions and searching for answers - the evidence based approach.

PubMed

Haroon, Munib; Phillips, Robert

2010-04-01

Evidence based medicine (EBM) consists of four separate processes. Asking a clinical question Locating the evidence Appraising and synthesizing the evidence Applying the evidence Most people are familiar with the third step but not so familiar with the first two. Well-designed clinical questions can help clarify in a clinicians mind exactly what information is being sought and also help with the search. This clinical question can be framed around the PICO format. With a well-structured PICO information can then be located in a timely manner using the concept of Haynes's 5 S's and a range of websites including trial registers and meta-search engines.

Human Interface to Netcentricity

DTIC Science & Technology

2006-06-01

experiencing. This is a radically different approach than using a federated search engine to bring back all relevant documents. The search engine...not be any closer to answering their question. More importantly, if they only have access to a 22 federated search , the program does not have the

The Google Online Marketing Challenge: Real Clients, Real Money, Real Ads and Authentic Learning

ERIC Educational Resources Information Center

Miko, John S.

2014-01-01

Search marketing is the process of utilizing search engines to drive traffic to a Web site through both paid and unpaid efforts. One potential paid component of a search marketing strategy is the use of a pay-per-click (PPC) advertising campaign in which advertisers pay search engine hosts only when their advertisement is clicked. This paper…

Information Retrieval for Education: Making Search Engines Language Aware

ERIC Educational Resources Information Center

Ott, Niels; Meurers, Detmar

2010-01-01

Search engines have been a major factor in making the web the successful and widely used information source it is today. Generally speaking, they make it possible to retrieve web pages on a topic specified by the keywords entered by the user. Yet web searching currently does not take into account which of the search results are comprehensible for…

Evaluation of an open source tool for indexing and searching enterprise radiology and pathology reports

NASA Astrophysics Data System (ADS)

Kim, Woojin; Boonn, William

2010-03-01

Data mining of existing radiology and pathology reports within an enterprise health system can be used for clinical decision support, research, education, as well as operational analyses. In our health system, the database of radiology and pathology reports exceeds 13 million entries combined. We are building a web-based tool to allow search and data analysis of these combined databases using freely available and open source tools. This presentation will compare performance of an open source full-text indexing tool to MySQL's full-text indexing and searching and describe implementation procedures to incorporate these capabilities into a radiology-pathology search engine.

Maritime Domain Awareness via Agent Learning and Collaboration

DTIC Science & Technology

2010-06-24

available search engines (e.g. Google-like search) are based on popularity or authority scores, which are proven to be useful in marketing and advertising applications...Useful in  marketing   and   advertising  applications  – Not as useful for intelligence applications  – Finding anomalous information can be the goal  • Our

Development of a One-Stop Data Search and Discovery Engine using Ontologies for Semantic Mappings (HydroSeek)

NASA Astrophysics Data System (ADS)

Piasecki, M.; Beran, B.

2007-12-01

Search engines have changed the way we see the Internet. The ability to find the information by just typing in keywords was a big contribution to the overall web experience. While the conventional search engine methodology worked well for textual documents, locating scientific data remains a problem since they are stored in databases not readily accessible by search engine bots. Considering different temporal, spatial and thematic coverage of different databases, especially for interdisciplinary research it is typically necessary to work with multiple data sources. These sources can be federal agencies which generally offer national coverage or regional sources which cover a smaller area with higher detail. However for a given geographic area of interest there often exists more than one database with relevant data. Thus being able to query multiple databases simultaneously is a desirable feature that would be tremendously useful for scientists. Development of such a search engine requires dealing with various heterogeneity issues. In scientific databases, systems often impose controlled vocabularies which ensure that they are generally homogeneous within themselves but are semantically heterogeneous when moving between different databases. This defines the boundaries of possible semantic related problems making it easier to solve than with the conventional search engines that deal with free text. We have developed a search engine that enables querying multiple data sources simultaneously and returns data in a standardized output despite the aforementioned heterogeneity issues between the underlying systems. This application relies mainly on metadata catalogs or indexing databases, ontologies and webservices with virtual globe and AJAX technologies for the graphical user interface. Users can trigger a search of dozens of different parameters over hundreds of thousands of stations from multiple agencies by providing a keyword, a spatial extent, i.e. a bounding box, and a temporal bracket. As part of this development we have also added an environment that allows users to do some of the semantic tagging, i.e. the linkage of a variable name (which can be anything they desire) to defined concepts in the ontology structure which in turn provides the backbone of the search engine.

Estimating search engine index size variability: a 9-year longitudinal study.

PubMed

van den Bosch, Antal; Bogers, Toine; de Kunder, Maurice

One of the determining factors of the quality of Web search engines is the size of their index. In addition to its influence on search result quality, the size of the indexed Web can also tell us something about which parts of the WWW are directly accessible to the everyday user. We propose a novel method of estimating the size of a Web search engine's index by extrapolating from document frequencies of words observed in a large static corpus of Web pages. In addition, we provide a unique longitudinal perspective on the size of Google and Bing's indices over a nine-year period, from March 2006 until January 2015. We find that index size estimates of these two search engines tend to vary dramatically over time, with Google generally possessing a larger index than Bing. This result raises doubts about the reliability of previous one-off estimates of the size of the indexed Web. We find that much, if not all of this variability can be explained by changes in the indexing and ranking infrastructure of Google and Bing. This casts further doubt on whether Web search engines can be used reliably for cross-sectional webometric studies.

Engineering Bacteria to Search for Specific Concentrations of Molecules by a Systematic Synthetic Biology Design Method

PubMed Central

Chen, Bor-Sen

2016-01-01

Bacteria navigate environments full of various chemicals to seek favorable places for survival by controlling the flagella’s rotation using a complicated signal transduction pathway. By influencing the pathway, bacteria can be engineered to search for specific molecules, which has great potential for application to biomedicine and bioremediation. In this study, genetic circuits were constructed to make bacteria search for a specific molecule at particular concentrations in their environment through a synthetic biology method. In addition, by replacing the “brake component” in the synthetic circuit with some specific sensitivities, the bacteria can be engineered to locate areas containing specific concentrations of the molecule. Measured by the swarm assay qualitatively and microfluidic techniques quantitatively, the characteristics of each “brake component” were identified and represented by a mathematical model. Furthermore, we established another mathematical model to anticipate the characteristics of the “brake component”. Based on this model, an abundant component library can be established to provide adequate component selection for different searching conditions without identifying all components individually. Finally, a systematic design procedure was proposed. Following this systematic procedure, one can design a genetic circuit for bacteria to rapidly search for and locate different concentrations of particular molecules by selecting the most adequate “brake component” in the library. Moreover, following simple procedures, one can also establish an exclusive component library suitable for other cultivated environments, promoter systems, or bacterial strains. PMID:27096615

Textpresso: An Ontology-Based Information Retrieval and Extraction System for Biological Literature

PubMed Central

Müller, Hans-Michael; Kenny, Eimear E

2004-01-01

We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso's two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc.) and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., biological process, etc.). Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquely named genes and an interaction term, the ontology confers a 3-fold increase of search efficiency. Textpresso currently focuses on Caenorhabditis elegans literature, with 3,800 full text articles and 16,000 abstracts. The lexicon of the ontology contains 14,500 entries, each of which includes all versions of a specific word or phrase, and it includes all categories of the Gene Ontology database. Textpresso is a useful curation tool, as well as search engine for researchers, and can readily be extended to other organism-specific corpora of text. Textpresso can be accessed at http://www.textpresso.org or via WormBase at http://www.wormbase.org. PMID:15383839

Collaborative search in electronic health records

PubMed Central

Mei, Qiaozhu; Hanauer, David A

2011-01-01

Objective A full-text search engine can be a useful tool for augmenting the reuse value of unstructured narrative data stored in electronic health records (EHR). A prominent barrier to the effective utilization of such tools originates from users' lack of search expertise and/or medical-domain knowledge. To mitigate the issue, the authors experimented with a ‘collaborative search’ feature through a homegrown EHR search engine that allows users to preserve their search knowledge and share it with others. This feature was inspired by the success of many social information-foraging techniques used on the web that leverage users' collective wisdom to improve the quality and efficiency of information retrieval. Design The authors conducted an empirical evaluation study over a 4-year period. The user sample consisted of 451 academic researchers, medical practitioners, and hospital administrators. The data were analyzed using a social-network analysis to delineate the structure of the user collaboration networks that mediated the diffusion of knowledge of search. Results The users embraced the concept with considerable enthusiasm. About half of the EHR searches processed by the system (0.44 million) were based on stored search knowledge; 0.16 million utilized shared knowledge made available by other users. The social-network analysis results also suggest that the user-collaboration networks engendered by the collaborative search feature played an instrumental role in enabling the transfer of search knowledge across people and domains. Conclusion Applying collaborative search, a social information-foraging technique popularly used on the web, may provide the potential to improve the quality and efficiency of information retrieval in healthcare. PMID:21486887

OS2: Oblivious similarity based searching for encrypted data outsourced to an untrusted domain

PubMed Central

Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Ramzan, Naeem

2017-01-01

Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search (OS2) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, OS2 ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables OS2 to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of OS2 is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations. PMID:28692697

[Formula: see text]: Oblivious similarity based searching for encrypted data outsourced to an untrusted domain.

PubMed

Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Ramzan, Naeem; Khan, Wajahat Ali

2017-01-01

Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search ([Formula: see text]) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, [Formula: see text] ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables [Formula: see text] to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of [Formula: see text] is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations.

FOAMSearch.net: A custom search engine for emergency medicine and critical care.

PubMed

Raine, Todd; Thoma, Brent; Chan, Teresa M; Lin, Michelle

2015-08-01

The number of online resources read by and pertinent to clinicians has increased dramatically. However, most healthcare professionals still use mainstream search engines as their primary port of entry to the resources on the Internet. These search engines use algorithms that do not make it easy to find clinician-oriented resources. FOAMSearch, a custom search engine (CSE), was developed to find relevant, high-quality online resources for emergency medicine and critical care (EMCC) clinicians. Using Google™ algorithms, it searches a vetted list of >300 blogs, podcasts, wikis, knowledge translation tools, clinical decision support tools and medical journals. Utilisation has increased progressively to >3000 users/month since its launch in 2011. Further study of the role of CSEs to find medical resources is needed, and it might be possible to develop similar CSEs for other areas of medicine. © 2015 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

[Study of the health food information for cancer patients on Japanese websites].

PubMed

Kishimoto, Keiko; Yoshino, Chie; Fukushima, Noriko

2010-08-01

The aim of this paper is to evaluate the reliability of websites providing health food information for cancer patients and, to assess the status to get this information online. We used four common Japanese search engines (Yahoo!, Google, goo, and MSN) to look up websites on Dec. 2, 2008. The search keywords were "health food" and "cancer". The websites for the first 100 hits generated by each search engine were screened and extracted by three conditions. We extracted 64 unique websites by the result of retrieval, of which 54 websites had information about health food factors. The two scales were used to evaluate the quality of the content on 54 websites. On the scale of reliability of information on the Web, the average score was 2.69+/-1.70 (maximum 6) and the median was 2.5. The other scale was matter need to check whether listed to use safely this information. On this scale, the average score was 0.72+/-1.22 (maximum 5) and the median was 0. Three engines showed poor correlation between the ranking and the latter score. But several websites on the top indicated 0 score. Fifty-four websites were extracted with one to four engines and the average number of search engines was 1.9. The two scales were positively correlated with the number of search engines, but these correlations were very poor. Ranking high and extraction by multiple search engines were of minor benefit to pick out more reliable information.

Guiding Students to Answers: Query Recommendation

ERIC Educational Resources Information Center

Yilmazel, Ozgur

2011-01-01

This paper reports on a guided navigation system built on the textbook search engine developed at Anadolu University to support distance education students. The search engine uses Turkish Language specific language processing modules to enable searches over course material presented in Open Education Faculty textbooks. We implemented a guided…

An Annotated and Federated Digital Library of Marine Animal Sounds

DTIC Science & Technology

2005-01-01

of the annotations and the relevant segment delimitation points and linkages to other relevant metadata fields; e) search engines that support the...annotators to add information to the same recording, and search engines that permit either all-annotator or specific-annotator searches. To our knowledge

Knowledge Based Engineering for Spatial Database Management and Use

NASA Technical Reports Server (NTRS)

Peuquet, D. (Principal Investigator)

1984-01-01

The use of artificial intelligence techniques that are applicable to Geographic Information Systems (GIS) are examined. Questions involving the performance and modification to the database structure, the definition of spectra in quadtree structures and their use in search heuristics, extension of the knowledge base, and learning algorithm concepts are investigated.

Automated semantic indexing of figure captions to improve radiology image retrieval.

PubMed

Kahn, Charles E; Rubin, Daniel L

2009-01-01

We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals. The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine. Estimated precision was 0.897 (95% confidence interval, 0.857-0.937). Estimated recall was 0.930 (95% confidence interval, 0.838-1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone. Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval.

Brute-Force Approach for Mass Spectrometry-Based Variant Peptide Identification in Proteogenomics without Personalized Genomic Data

NASA Astrophysics Data System (ADS)

Ivanov, Mark V.; Lobas, Anna A.; Levitsky, Lev I.; Moshkovskii, Sergei A.; Gorshkov, Mikhail V.

2018-02-01

In a proteogenomic approach based on tandem mass spectrometry analysis of proteolytic peptide mixtures, customized exome or RNA-seq databases are employed for identifying protein sequence variants. However, the problem of variant peptide identification without personalized genomic data is important for a variety of applications. Following the recent proposal by Chick et al. (Nat. Biotechnol. 33, 743-749, 2015) on the feasibility of such variant peptide search, we evaluated two available approaches based on the previously suggested "open" search and the "brute-force" strategy. To improve the efficiency of these approaches, we propose an algorithm for exclusion of false variant identifications from the search results involving analysis of modifications mimicking single amino acid substitutions. Also, we propose a de novo based scoring scheme for assessment of identified point mutations. In the scheme, the search engine analyzes y-type fragment ions in MS/MS spectra to confirm the location of the mutation in the variant peptide sequence.

L1000CDS2: LINCS L1000 characteristic direction signatures search engine.

PubMed

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma'ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS 2 . The L1000CDS 2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS 2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS 2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS 2 , we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS 2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS 2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.

Search without Boundaries Using Simple APIs

USGS Publications Warehouse

Tong, Qi

2009-01-01

The U.S. Geological Survey (USGS) Library, where the author serves as the digital services librarian, is increasingly challenged to make it easier for users to find information from many heterogeneous information sources. Information is scattered throughout different software applications (i.e., library catalog, federated search engine, link resolver, and vendor websites), and each specializes in one thing. How could the library integrate the functionalities of one application with another and provide a single point of entry for users to search across? To improve the user experience, the library launched an effort to integrate the federated search engine into the library's intranet website. The result is a simple search box that leverages the federated search engine's built-in application programming interfaces (APIs). In this article, the author describes how this project demonstrated the power of APIs and their potential to be used by other enterprise search portals inside or outside of the library.

Searches Conducted for Engineers.

ERIC Educational Resources Information Center

Lorenz, Patricia

This paper reports an industrial information specialist's experience in performing online searches for engineers and surveys the databases used. Engineers seeking assistance fall into three categories: (1) those who recognize the value of online retrieval; (2) referrals by colleagues; and (3) those who do not seek help. As more successful searches…

FGMReview: design of a knowledge management tool on female genital mutilation.

PubMed

Martínez Pérez, Guillermo; Turetsky, Risa

2015-11-01

Web-based literature search engines may not be user-friendly for some readers searching for information on female genital mutilation. This is a traditional practice that has no health benefits, and about 140 million girls and women worldwide have undergone it. In 2012, the website FGMReview was created with the aim to offer a user-friendly, accessible, scalable, and innovative knowledge management tool specialized in female genital mutilation. The design of this website was guided by a conceptual model based on the use of benchmarking techniques and requirements engineering, an area of knowledge from the computer informatics field, influenced by the Transcultural Nursing model. The purpose of this article is to describe this conceptual model. Nurses and other health care providers can use this conceptual model to guide their methodological approach to design and launch other eHealth projects. © The Author(s) 2014.

DOE Office of Scientific and Technical Information (OSTI.GOV)

None Available

To make the web work better for science, OSTI has developed state-of-the-art technologies and services including a deep web search capability. The deep web includes content in searchable databases available to web users but not accessible by popular search engines, such as Google. This video provides an introduction to the deep web search engine.

"Just the Answers, Please": Choosing a Web Search Service.

ERIC Educational Resources Information Center

Feldman, Susan

1997-01-01

Presents guidelines for selecting World Wide Web search engines. Real-life questions were used to test six search engines. Queries sought company information, product reviews, medical information, foreign information, technical reports, and current events. Compares performance and features of AltaVista, Excite, HotBot, Infoseek, Lycos, and Open…

A Search Engine Features Comparison.

ERIC Educational Resources Information Center

Vorndran, Gerald

Until recently, the World Wide Web (WWW) public access search engines have not included many of the advanced commands, options, and features commonly available with the for-profit online database user interfaces, such as DIALOG. This study evaluates the features and characteristics common to both types of search interfaces, examines the Web search…

Next-Gen Search Engines

ERIC Educational Resources Information Center

Gupta, Amardeep

2005-01-01

Current search engines--even the constantly surprising Google--seem unable to leap the next big barrier in search: the trillions of bytes of dynamically generated data created by individual web sites around the world, or what some researchers call the "deep web." The challenge now is not information overload, but information overlook.…

Creating a Classroom Kaleidoscope with the World Wide Web.

ERIC Educational Resources Information Center

Quinlan, Laurie A.

1997-01-01

Discusses the elements of classroom Web presentations: planning; construction, including design tips; classroom use; and assessment. Lists 14 World Wide Web resources for K-12 teachers; Internet search tools (directories, search engines and meta-search engines); a Web glossary; and an example of HTML for a simple Web page. (PEN)

Large Scale IR Evaluation

ERIC Educational Resources Information Center

Pavlu, Virgil

2008-01-01

Today, search engines are embedded into all aspects of digital world: in addition to Internet search, all operating systems have integrated search engines that respond even as you type, even over the network, even on cell phones; therefore the importance of their efficacy and efficiency cannot be overstated. There are many open possibilities for…

A review of the reporting of web searching to identify studies for Cochrane systematic reviews.

PubMed

Briscoe, Simon

2018-03-01

The literature searches that are used to identify studies for inclusion in a systematic review should be comprehensively reported. This ensures that the literature searches are transparent and reproducible, which is important for assessing the strengths and weaknesses of a systematic review and re-running the literature searches when conducting an update review. Web searching using search engines and the websites of topically relevant organisations is sometimes used as a supplementary literature search method. Previous research has shown that the reporting of web searching in systematic reviews often lacks important details and is thus not transparent or reproducible. Useful details to report about web searching include the name of the search engine or website, the URL, the date searched, the search strategy, and the number of results. This study reviews the reporting of web searching to identify studies for Cochrane systematic reviews published in the 6-month period August 2016 to January 2017 (n = 423). Of these reviews, 61 reviews reported using web searching using a search engine or website as a literature search method. In the majority of reviews, the reporting of web searching was found to lack essential detail for ensuring transparency and reproducibility, such as the search terms. Recommendations are made on how to improve the reporting of web searching in Cochrane systematic reviews. Copyright © 2017 John Wiley & Sons, Ltd.

Curating the Web: Building a Google Custom Search Engine for the Arts

ERIC Educational Resources Information Center

Hennesy, Cody; Bowman, John

2008-01-01

Google's first foray onto the web made search simple and results relevant. With its Co-op platform, Google has taken another step toward dramatically increasing the relevancy of search results, further adapting the World Wide Web to local needs. Google Custom Search Engine, a tool on the Co-op platform, puts one in control of his or her own search…

Federated Search and the Library Web Site: A Study of Association of Research Libraries Member Web Sites

ERIC Educational Resources Information Center

Williams, Sarah C.

2010-01-01

The purpose of this study was to investigate how federated search engines are incorporated into the Web sites of libraries in the Association of Research Libraries. In 2009, information was gathered for each library in the Association of Research Libraries with a federated search engine. This included the name of the federated search service and…

MPA Portable: A Stand-Alone Software Package for Analyzing Metaproteome Samples on the Go.

PubMed

Muth, Thilo; Kohrs, Fabian; Heyer, Robert; Benndorf, Dirk; Rapp, Erdmann; Reichl, Udo; Martens, Lennart; Renard, Bernhard Y

2018-01-02

Metaproteomics, the mass spectrometry-based analysis of proteins from multispecies samples faces severe challenges concerning data analysis and results interpretation. To overcome these shortcomings, we here introduce the MetaProteomeAnalyzer (MPA) Portable software. In contrast to the original server-based MPA application, this newly developed tool no longer requires computational expertise for installation and is now independent of any relational database system. In addition, MPA Portable now supports state-of-the-art database search engines and a convenient command line interface for high-performance data processing tasks. While search engine results can easily be combined to increase the protein identification yield, an additional two-step workflow is implemented to provide sufficient analysis resolution for further postprocessing steps, such as protein grouping as well as taxonomic and functional annotation. Our new application has been developed with a focus on intuitive usability, adherence to data standards, and adaptation to Web-based workflow platforms. The open source software package can be found at https://github.com/compomics/meta-proteome-analyzer .

Semantic interpretation of search engine resultant

NASA Astrophysics Data System (ADS)

Nasution, M. K. M.

2018-01-01

In semantic, logical language can be interpreted in various forms, but the certainty of meaning is included in the uncertainty, which directly always influences the role of technology. One results of this uncertainty applies to search engines as user interfaces with information spaces such as the Web. Therefore, the behaviour of search engine results should be interpreted with certainty through semantic formulation as interpretation. Behaviour formulation shows there are various interpretations that can be done semantically either temporary, inclusion, or repeat.

Health search engine with e-document analysis for reliable search results.

PubMed

Gaudinat, Arnaud; Ruch, Patrick; Joubert, Michel; Uziel, Philippe; Strauss, Anne; Thonnet, Michèle; Baud, Robert; Spahni, Stéphane; Weber, Patrick; Bonal, Juan; Boyer, Celia; Fieschi, Marius; Geissbuhler, Antoine

2006-01-01

After a review of the existing practical solution available to the citizen to retrieve eHealth document, the paper describes an original specialized search engine WRAPIN. WRAPIN uses advanced cross lingual information retrieval technologies to check information quality by synthesizing medical concepts, conclusions and references contained in the health literature, to identify accurate, relevant sources. Thanks to MeSH terminology [1] (Medical Subject Headings from the U.S. National Library of Medicine) and advanced approaches such as conclusion extraction from structured document, reformulation of the query, WRAPIN offers to the user a privileged access to navigate through multilingual documents without language or medical prerequisites. The results of an evaluation conducted on the WRAPIN prototype show that results of the WRAPIN search engine are perceived as informative 65% (59% for a general-purpose search engine), reliable and trustworthy 72% (41% for the other engine) by users. But it leaves room for improvement such as the increase of database coverage, the explanation of the original functionalities and an audience adaptability. Thanks to evaluation outcomes, WRAPIN is now in exploitation on the HON web site (http://www.healthonnet.org), free of charge. Intended to the citizen it is a good alternative to general-purpose search engines when the user looks up trustworthy health and medical information or wants to check automatically a doubtful content of a Web page.

AphidBase: A centralized bioinformatic resource for annotation of the pea aphid genome

PubMed Central

Legeai, Fabrice; Shigenobu, Shuji; Gauthier, Jean-Pierre; Colbourne, John; Rispe, Claude; Collin, Olivier; Richards, Stephen; Wilson, Alex C. C.; Tagu, Denis

2015-01-01

AphidBase is a centralized bioinformatic resource that was developed to facilitate community annotation of the pea aphid genome by the International Aphid Genomics Consortium (IAGC). The AphidBase Information System designed to organize and distribute genomic data and annotations for a large international community was constructed using open source software tools from the Generic Model Organism Database (GMOD). The system includes Apollo and GBrowse utilities as well as a wiki, blast search capabilities and a full text search engine. AphidBase strongly supported community cooperation and coordination in the curation of gene models during community annotation of the pea aphid genome. AphidBase can be accessed at http://www.aphidbase.com. PMID:20482635

SearchGUI: An open-source graphical user interface for simultaneous OMSSA and X!Tandem searches.

PubMed

Vaudel, Marc; Barsnes, Harald; Berven, Frode S; Sickmann, Albert; Martens, Lennart

2011-03-01

The identification of proteins by mass spectrometry is a standard technique in the field of proteomics, relying on search engines to perform the identifications of the acquired spectra. Here, we present a user-friendly, lightweight and open-source graphical user interface called SearchGUI (http://searchgui.googlecode.com), for configuring and running the freely available OMSSA (open mass spectrometry search algorithm) and X!Tandem search engines simultaneously. Freely available under the permissible Apache2 license, SearchGUI is supported on Windows, Linux and OSX. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Abyss or Shelter? On the Relevance of Web Search Engines' Search Results When People Google for Suicide.

PubMed

Haim, Mario; Arendt, Florian; Scherr, Sebastian

2017-02-01

Despite evidence that suicide rates can increase after suicides are widely reported in the media, appropriate depictions of suicide in the media can help people to overcome suicidal crises and can thus elicit preventive effects. We argue on the level of individual media users that a similar ambivalence can be postulated for search results on online suicide-related search queries. Importantly, the filter bubble hypothesis (Pariser, 2011) states that search results are biased by algorithms based on a person's previous search behavior. In this study, we investigated whether suicide-related search queries, including either potentially suicide-preventive or -facilitative terms, influence subsequent search results. This might thus protect or harm suicidal Internet users. We utilized a 3 (search history: suicide-related harmful, suicide-related helpful, and suicide-unrelated) × 2 (reactive: clicking the top-most result link and no clicking) experimental design applying agent-based testing. While findings show no influences either of search histories or of reactivity on search results in a subsequent situation, the presentation of a helpline offer raises concerns about possible detrimental algorithmic decision-making: Algorithms "decided" whether or not to present a helpline, and this automated decision, then, followed the agent throughout the rest of the observation period. Implications for policy-making and search providers are discussed.

Comfort and human factors in office and residential settings. (Latest citations from the NTIS data base). Published Search

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-04-01

The bibliography contains citations concerning human factors engineering, anthropometry, and ergonomics as they relate to human comfort in the office and home. Human requirements, including ventilation, temperature control, and lighting, are considered. Research regarding environmental architecture, and engineering, safety, and convenience aspects are discussed. (Contains a minimum of 142 citations and includes a subject term index and title list.)

A Comparison of Source Code Plagiarism Detection Engines

NASA Astrophysics Data System (ADS)

Lancaster, Thomas; Culwin, Fintan

2004-06-01

Automated techniques for finding plagiarism in student source code submissions have been in use for over 20 years and there are many available engines and services. This paper reviews the literature on the major modern detection engines, providing a comparison of them based upon the metrics and techniques they deploy. Generally the most common and effective techniques are seen to involve tokenising student submissions then searching pairs of submissions for long common substrings, an example of what is defined to be a paired structural metric. Computing academics are recommended to use one of the two Web-based detection engines, MOSS and JPlag. It is shown that whilst detection is well established there are still places where further research would be useful, particularly where visual support of the investigation process is possible.

Locus Guard Pilot

NASA Astrophysics Data System (ADS)

Chandrashekar, Varsha; B, Prabadevi

2017-11-01

Providing services to user is the main functionality of every search engine. Recently services based on users’ current location has also been enabled with the help of GPS in every smartphone. But how safe are their searches and how trustworthy is the search engine. Why are users tracked even when they turn off the tracking. Where lies the solution. Unless there is a security system to prevent ad trackers from misusing user’ s location, any application which relies on user’ s location will be of no use. We know that location information is highly sensitive personal data. Knowing where a person was at a particular time, one can infer his/her personal activities, political views, health status, and launch unsolicited advertising, physical attacks or harassment. Therefore, mechanisms to preserve users' privacy and anonymity are mandatory in any application that involves users’ location. So there comes the need to hide the location of the users. This proposed application aims to implement some of the features required for preserving users’ privacy and also a secure user login so that services provided to users can be used by them without danger of their searches being misused.

DRUMS: a human disease related unique gene mutation search engine.

PubMed

Li, Zuofeng; Liu, Xingnan; Wen, Jingran; Xu, Ye; Zhao, Xin; Li, Xuan; Liu, Lei; Zhang, Xiaoyan

2011-10-01

With the completion of the human genome project and the development of new methods for gene variant detection, the integration of mutation data and its phenotypic consequences has become more important than ever. Among all available resources, locus-specific databases (LSDBs) curate one or more specific genes' mutation data along with high-quality phenotypes. Although some genotype-phenotype data from LSDB have been integrated into central databases little effort has been made to integrate all these data by a search engine approach. In this work, we have developed disease related unique gene mutation search engine (DRUMS), a search engine for human disease related unique gene mutation as a convenient tool for biologists or physicians to retrieve gene variant and related phenotype information. Gene variant and phenotype information were stored in a gene-centred relational database. Moreover, the relationships between mutations and diseases were indexed by the uniform resource identifier from LSDB, or another central database. By querying DRUMS, users can access the most popular mutation databases under one interface. DRUMS could be treated as a domain specific search engine. By using web crawling, indexing, and searching technologies, it provides a competitively efficient interface for searching and retrieving mutation data and their relationships to diseases. The present system is freely accessible at http://www.scbit.org/glif/new/drums/index.html. © 2011 Wiley-Liss, Inc.

Image Search Reranking With Hierarchical Topic Awareness.

PubMed

Tian, Xinmei; Yang, Linjun; Lu, Yijuan; Tian, Qi; Tao, Dacheng

2015-10-01

With much attention from both academia and industrial communities, visual search reranking has recently been proposed to refine image search results obtained from text-based image search engines. Most of the traditional reranking methods cannot capture both relevance and diversity of the search results at the same time. Or they ignore the hierarchical topic structure of search result. Each topic is treated equally and independently. However, in real applications, images returned for certain queries are naturally in hierarchical organization, rather than simple parallel relation. In this paper, a new reranking method "topic-aware reranking (TARerank)" is proposed. TARerank describes the hierarchical topic structure of search results in one model, and seamlessly captures both relevance and diversity of the image search results simultaneously. Through a structured learning framework, relevance and diversity are modeled in TARerank by a set of carefully designed features, and then the model is learned from human-labeled training samples. The learned model is expected to predict reranking results with high relevance and diversity for testing queries. To verify the effectiveness of the proposed method, we collect an image search dataset and conduct comparison experiments on it. The experimental results demonstrate that the proposed TARerank outperforms the existing relevance-based and diversified reranking methods.

Engine Data Interpretation System (EDIS), phase 2

NASA Technical Reports Server (NTRS)

Cost, Thomas L.; Hofmann, Martin O.

1991-01-01

A prototype of an expert system was developed which applies qualitative constraint-based reasoning to the task of post-test analysis of data resulting from a rocket engine firing. Data anomalies are detected and corresponding faults are diagnosed. Engine behavior is reconstructed using measured data and knowledge about engine behavior. Knowledge about common faults guides but does not restrict the search for the best explanation in terms of hypothesized faults. The system contains domain knowledge about the behavior of common rocket engine components and was configured for use with the Space Shuttle Main Engine (SSME). A graphical user interface allows an expert user to intimately interact with the system during diagnosis. The system was applied to data taken during actual SSME tests where data anomalies were observed.

Re-ranking via User Feedback: Georgetown University at TREC 2015 DD Track

DTIC Science & Technology

2015-11-20

Re-ranking via User Feedback: Georgetown University at TREC 2015 DD Track Jiyun Luo and Hui Yang Department of Computer Science, Georgetown...involved in a search process, the user and the search engine. In TREC DD , the user is modeled by a simulator, called “jig”. The jig and the search engine...simulating user is provided by TREC 2015 DD Track organizer, and is called “jig”. There are 118 search topics in total. For each search topic, a short

Collection of Medical Original Data with Search Engine for Decision Support.

PubMed

Orthuber, Wolfgang

2016-01-01

Medicine is becoming more and more complex and humans can capture total medical knowledge only partially. For specific access a high resolution search engine is demonstrated, which allows besides conventional text search also search of precise quantitative data of medical findings, therapies and results. Users can define metric spaces ("Domain Spaces", DSs) with all searchable quantitative data ("Domain Vectors", DSs). An implementation of the search engine is online in http://numericsearch.com. In future medicine the doctor could make first a rough diagnosis and check which fine diagnostics (quantitative data) colleagues had collected in such a case. Then the doctor decides about fine diagnostics and results are sent (half automatically) to the search engine which filters a group of patients which best fits to these data. In this specific group variable therapies can be checked with associated therapeutic results, like in an individual scientific study for the current patient. The statistical (anonymous) results could be used for specific decision support. Reversely the therapeutic decision (in the best case with later results) could be used to enhance the collection of precise pseudonymous medical original data which is used for better and better statistical (anonymous) search results.

Lyceum: A Multi-Protocol Digital Library Gateway

NASA Technical Reports Server (NTRS)

Maa, Ming-Hokng; Nelson, Michael L.; Esler, Sandra L.

1997-01-01

Lyceum is a prototype scalable query gateway that provides a logically central interface to multi-protocol and physically distributed, digital libraries of scientific and technical information. Lyceum processes queries to multiple syntactically distinct search engines used by various distributed information servers from a single logically central interface without modification of the remote search engines. A working prototype (http://www.larc.nasa.gov/lyceum/) demonstrates the capabilities, potentials, and advantages of this type of meta-search engine by providing access to over 50 servers covering over 20 disciplines.

Start Your Search Engines. Part 2: When Image is Everything, Here are Some Great Ways to Find One

ERIC Educational Resources Information Center

Adam, Anna; Mowers, Helen

2008-01-01

There is no doubt that Google is great for finding images. Simply head to its home page, click the "Images" link, enter criteria in the search box, and--voila! In this article, the authors share some of their other favorite search engines for finding images. To make sure the desired images are available for educational use, consider searching for…

Side effects of radiotherapy in breast cancer patients : The Internet as an information source.

PubMed

Janssen, S; Käsmann, L; Fahlbusch, F B; Rades, D; Vordermark, D

2018-02-01

Breast cancer is the most common cancer type among women necessitating adjuvant radiotherapy. As the Internet has become a major source of information for cancer patients, this study aimed to evaluate the quality of websites giving information on side effects of radiotherapy for breast cancer patients. A patients' search for the English terms "breast cancer - radiotherapy - side effects" and the corresponding German terms "Brustkrebs - Strahlentherapie - Nebenwirkungen" was carried out twice (5 months apart) using the search engine Google. The first 30 search results each were evaluated using the validated 16-question DISCERN Plus instrument, the Health on the Net Code of Conduct (HONcode) certification and the Journal of the American Medical Association (JAMA) benchmark criteria. The overall quality (DISCERN score) of the retrieved websites was further compared to queries via Bing and Yahoo search engines. The DISCERN score showed a great range, with the majority of websites ranking fair to poor. Significantly superior results were found for English websites, particularly for webpages run by hospitals/universities and nongovernmental organizations (NGO), when compared to the respective German categories. In general, only a minority of websites met all JAMA benchmarks and was HONcode certified (both languages). We did not determine a relevant temporal change in website ranking among the top ten search hits, while significant variation occurred thereafter. Mean overall DISCERN score was similar between the various search engines. The Internet can give breast cancer patients seeking information on side effects of radiotherapy an overview. However, based on the currently low overall quality of websites and the lack of transparency for the average layperson, we emphasize the value of personal contact with the treating radio-oncologist in order to integrate and interpret the information found online.

Deep Web video

ScienceCinema

None Available

2018-02-06

To make the web work better for science, OSTI has developed state-of-the-art technologies and services including a deep web search capability. The deep web includes content in searchable databases available to web users but not accessible by popular search engines, such as Google. This video provides an introduction to the deep web search engine.

Paying Your Way to the Top: Search Engine Advertising.

ERIC Educational Resources Information Center

Scott, David M.

2003-01-01

Explains how organizations can buy listings on major Web search engines, making it the fastest growing form of advertising. Highlights include two network models, Google and Overture; bidding on phrases to buy as links to use with ads; ad ranking; benefits for small businesses; and paid listings versus regular search results. (LRW)

Improving Web Search for Difficult Queries

ERIC Educational Resources Information Center

Wang, Xuanhui

2009-01-01

Search engines have now become essential tools in all aspects of our life. Although a variety of information needs can be served very successfully, there are still a lot of queries that search engines can not answer very effectively and these queries always make users feel frustrated. Since it is quite often that users encounter such "difficult…

Design and Implementation of a Prototype Ontology Aided Knowledge Discovery Assistant (OAKDA) Application

DTIC Science & Technology

2006-12-01

speed of search engines improves the efficiency of such methods, effectiveness is not improved. The objective of this thesis is to construct and test...interest, users are assisted in finding a relevant set of key terms that will aid the search engines in narrowing, widening, or refocusing a Web search

Search Engines: A Primer on Finding Information on the World Wide Web.

ERIC Educational Resources Information Center

Maddux, Cleborne

1996-01-01

Presents an annotated list of several World Wide Web search engines, including Yahoo, Infoseek, Alta Vista, Magellan, Lycos, Webcrawler, Excite, Deja News, and the LISZT Directory of discussion groups. Uniform Resource Locators (URLs) are included. Discussion assesses performance and describes rules and syntax for refining or limiting a search.…

Where Do I Find It?--An Internet Glossary.

ERIC Educational Resources Information Center

Del Monte, Erin; Manso, Angela

2001-01-01

Lists 13 different Internet search engines that might be of interest to educators, including: AOL Search, Alta Vista, Google, Lycos, Northern Light, and Yahoo. Gives a brief description of each search engine's capabilities, strengths, and weaknesses and includes Web addresses of U.S. government offices, including the U.S. Department of Education.…

Web Service

MedlinePlus

... on the relevance score as determined by the search engine. Generally, the first document in the first results ... Spanish . snippet Brief result summary generated by the search engine that provides a preview of the relevant content ...

Examining the themes of STD-related Internet searches to increase specificity of disease forecasting using Internet search terms.

PubMed

Johnson, Amy K; Mikati, Tarek; Mehta, Supriya D

2016-11-09

US surveillance of sexually transmitted diseases (STDs) is often delayed and incomplete which creates missed opportunities to identify and respond to trends in disease. Internet search engine data has the potential to be an efficient, economical and representative enhancement to the established surveillance system. Google Trends allows the download of de-identified search engine data, which has been used to demonstrate the positive and statistically significant association between STD-related search terms and STD rates. In this study, search engine user content was identified by surveying specific exposure groups of individuals (STD clinic patients and university students) aged 18-35. Participants were asked to list the terms they use to search for STD-related information. Google Correlate was used to validate search term content. On average STD clinic participant queries were longer compared to student queries. STD clinic participants were more likely to report using search terms that were related to symptomatology such as describing symptoms of STDs, while students were more likely to report searching for general information. These differences in search terms by subpopulation have implications for STD surveillance in populations at most risk for disease acquisition.

Recommendations for a Habitability Data Base.

ERIC Educational Resources Information Center

Illinois Univ., Urbana. Library Research Center.

A prototype Habitability Data Base was developed for the United States Army Corps of Engineers. From a review of selected Army documents, standards in the form of goals or architectural criteria were identified as significant to man-environment relations (MER). A search of appropriate information systems was conducted to retrieve a minimum of 500…

An overview of expert systems. [artificial intelligence

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1982-01-01

An expert system is defined and its basic structure is discussed. The knowledge base, the inference engine, and uses of expert systems are discussed. Architecture is considered, including choice of solution direction, reasoning in the presence of uncertainty, searching small and large search spaces, handling large search spaces by transforming them and by developing alternative or additional spaces, and dealing with time. Existing expert systems are reviewed. Tools for building such systems, construction, and knowledge acquisition and learning are discussed. Centers of research and funding sources are listed. The state-of-the-art, current problems, required research, and future trends are summarized.

Different methods of dentin processing for application in bone tissue engineering: A systematic review.

PubMed

Tabatabaei, Fahimeh Sadat; Tatari, Saeed; Samadi, Ramin; Moharamzadeh, Keyvan

2016-10-01

Dentin has become an interesting potential biomaterial for tissue engineering of oral hard tissues. It can be used as a scaffold or as a source of growth factors in bone tissue engineering. Different forms of dentin have been studied for their potential use as bone substitutes. Here, we systematically review different methods of dentin preparation and the efficacy of processed dentin in bone tissue engineering. An electronic search was carried out in PubMed and Scopus databases for articles published from 2000 to 2016. Studies on dentin preparation for application in bone tissue engineering were selected. The initial search yielded a total of 1045 articles, of which 37 were finally selected. Review of studies showed that demineralization was the most commonly used dentin preparation process for use in tissue engineering. Dentin extract, dentin particles (tooth ash), freeze-dried dentin, and denatured dentin are others method of dentin preparation. Based on our literature review, we can conclude that preparation procedure and the size and shape of dentin particles play an important role in its osteoinductive and osteoconductive properties. Standardization of these methods is important to draw a conclusion in this regard. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 2616-2627, 2016. © 2016 Wiley Periodicals, Inc.

Textual appropriation in engineering master's theses: a preliminary study.

PubMed

Eckel, Edward J

2011-09-01

In the thesis literature review, an engineering graduate student is expected to place original research in the context of previous work by other researchers. However, for some students, particularly those for whom English is a second language, the literature review may be a mixture of original writing and verbatim source text appropriated without quotations. Such problematic use of source material leaves students vulnerable to an accusation of plagiarism, which carries severe consequences. Is such textual appropriation common in engineering master's writing? Furthermore, what, if anything, can be concluded when two texts have been found to have textual material in common? Do existing definitions of plagiarism provide a sufficient framework for determining if an instance of copying is transgressive or not? In a preliminary attempt to answer these questions, text strings from a random sample of 100 engineering master's theses from the ProQuest Dissertations and Theses database were searched for appropriated verbatim source text using the Google search engine. The results suggest that textual borrowing may indeed be a common feature of the master's engineering literature review, raising questions about the ability of graduate students to synthesize the literature. The study also illustrates the difficulties of making a determination of plagiarism based on simple textual similarity. A context-specific approach is recommended when dealing with any instance of apparent copying.

Searching the world wide Web

PubMed

Lawrence; Giles

1998-04-03

The coverage and recency of the major World Wide Web search engines was analyzed, yielding some surprising results. The coverage of any one engine is significantly limited: No single engine indexes more than about one-third of the "indexable Web," the coverage of the six engines investigated varies by an order of magnitude, and combining the results of the six engines yields about 3.5 times as many documents on average as compared with the results from only one engine. Analysis of the overlap between pairs of engines gives an estimated lower bound on the size of the indexable Web of 320 million pages.

Public hospital quality report awareness: evidence from National and Californian Internet searches and social media mentions, 2012.

PubMed

Huesch, Marco D; Currid-Halkett, Elizabeth; Doctor, Jason N

2014-03-11

Publicly available hospital quality reports seek to inform consumers of important healthcare quality and affordability attributes, and may inform consumer decision-making. To understand how much consumers search for such information online on one Internet search engine, whether they mention such information in social media and how positively they view this information. A leading Internet search engine (Google) was the main focus of the study. Google Trends and Google Adwords keyword analyses were performed for national and Californian searches between 1 August 2012 and 31 July 2013 for keywords related to 'top hospital', best hospital', and 'hospital quality', as well as for six specific hospital quality reports. Separately, a proprietary social media monitoring tool was used to investigate blog, forum, social media and traditional media mentions of, and sentiment towards, major public reports of hospital quality in California in 2012. (1) Counts of searches for keywords performed on Google; (2) counts of and (3) sentiment of mentions of public reports on social media. National Google search volume for 75 hospital quality-related terms averaged 610 700 searches per month with strong variation by keyword and by state. A commercial report (Healthgrades) was more commonly searched for nationally on Google than the federal government's Hospital Compare, which otherwise dominated quality-related search terms. Social media references in California to quality reports were generally few, and commercially produced hospital quality reports were more widely mentioned than state (Office of Statewide Healthcare Planning and Development (OSHPD)), or non-profit (CalHospitalCompare) reports. Consumers are somewhat aware of hospital quality based on Internet search activity and social media disclosures. Public stakeholders may be able to broaden their quality dissemination initiatives by advertising on Google or Twitter and using social media interactively with consumers looking for relevant information.

Enhanced optical alignment of a digital micro mirror device through Bayesian adaptive exploration

NASA Astrophysics Data System (ADS)

Wynne, Kevin B.; Knuth, Kevin H.; Petruccelli, Jonathan

2017-12-01

As the use of Digital Micro Mirror Devices (DMDs) becomes more prevalent in optics research, the ability to precisely locate the Fourier "footprint" of an image beam at the Fourier plane becomes a pressing need. In this approach, Bayesian adaptive exploration techniques were employed to characterize the size and position of the beam on a DMD located at the Fourier plane. It couples a Bayesian inference engine with an inquiry engine to implement the search. The inquiry engine explores the DMD by engaging mirrors and recording light intensity values based on the maximization of the expected information gain. Using the data collected from this exploration, the Bayesian inference engine updates the posterior probability describing the beam's characteristics. The process is iterated until the beam is located to within the desired precision. This methodology not only locates the center and radius of the beam with remarkable precision but accomplishes the task in far less time than a brute force search. The employed approach has applications to system alignment for both Fourier processing and coded aperture design.

How to Find Reliable ENT Info

MedlinePlus

... about your condition may be difficult. Most search engines and directories do not rank information from your ... you to buy its product paid the search engine company to list it near the top. Your ...

A novel architecture for information retrieval system based on semantic web

NASA Astrophysics Data System (ADS)

Zhang, Hui

2011-12-01

Nowadays, the web has enabled an explosive growth of information sharing (there are currently over 4 billion pages covering most areas of human endeavor) so that the web has faced a new challenge of information overhead. The challenge that is now before us is not only to help people locating relevant information precisely but also to access and aggregate a variety of information from different resources automatically. Current web document are in human-oriented formats and they are suitable for the presentation, but machines cannot understand the meaning of document. To address this issue, Berners-Lee proposed a concept of semantic web. With semantic web technology, web information can be understood and processed by machine. It provides new possibilities for automatic web information processing. A main problem of semantic web information retrieval is that when these is not enough knowledge to such information retrieval system, the system will return to a large of no sense result to uses due to a huge amount of information results. In this paper, we present the architecture of information based on semantic web. In addiction, our systems employ the inference Engine to check whether the query should pose to Keyword-based Search Engine or should pose to the Semantic Search Engine.

International use of an academic nephrology World Wide Web site: from medical information resource to business tool.

PubMed

Abbott, Kevin C; Oliver, David K; Boal, Thomas R; Gadiyak, Grigorii; Boocks, Carl; Yuan, Christina M; Welch, Paul G; Poropatich, Ronald K

2002-04-01

Studies of the use of the World Wide Web to obtain medical knowledge have largely focused on patients. In particular, neither the international use of academic nephrology World Wide Web sites (websites) as primary information sources nor the use of search engines (and search strategies) to obtain medical information have been described. Visits ("hits") to the Walter Reed Army Medical Center (WRAMC) Nephrology Service website from April 30, 2000, to March 14, 2001, were analyzed for the location of originating source using Webtrends, and search engines (Google, Lycos, etc.) were analyzed manually for search strategies used. From April 30, 2000 to March 14, 2001, the WRAMC Nephrology Service website received 1,007,103 hits and 12,175 visits. These visits were from 33 different countries, and the most frequent regions were Western Europe, Asia, Australia, the Middle East, Pacific Islands, and South America. The most frequent organization using the site was the military Internet system, followed by America Online and automated search programs of online search engines, most commonly Google. The online lecture series was the most frequently visited section of the website. Search strategies used in search engines were extremely technical. The use of "robots" by standard Internet search engines to locate websites, which may be blocked by mandatory registration, has allowed users worldwide to access the WRAMC Nephrology Service website to answer very technical questions. This suggests that it is being used as an alternative to other primary sources of medical information and that the use of mandatory registration may hinder users from finding valuable sites. With current Internet technology, even a single service can become a worldwide information resource without sacrificing its primary customers.

Automatic Concept-Based Query Expansion Using Term Relational Pathways Built from a Collection-Specific Association Thesaurus

ERIC Educational Resources Information Center

Lyall-Wilson, Jennifer Rae

2013-01-01

The dissertation research explores an approach to automatic concept-based query expansion to improve search engine performance. It uses a network-based approach for identifying the concept represented by the user's query and is founded on the idea that a collection-specific association thesaurus can be used to create a reasonable representation of…

Detecting the Norovirus Season in Sweden Using Search Engine Data – Meeting the Needs of Hospital Infection Control Teams

PubMed Central

Edelstein, Michael; Wallensten, Anders; Zetterqvist, Inga; Hulth, Anette

2014-01-01

Norovirus outbreaks severely disrupt healthcare systems. We evaluated whether Websök, an internet-based surveillance system using search engine data, improved norovirus surveillance and response in Sweden. We compared Websök users' characteristics with the general population, cross-correlated weekly Websök searches with laboratory notifications between 2006 and 2013, compared the time Websök and laboratory data crossed the epidemic threshold and surveyed infection control teams about their perception and use of Websök. Users of Websök were not representative of the general population. Websök correlated with laboratory data (b = 0.88-0.89) and gave an earlier signal to the onset of the norovirus season compared with laboratory-based surveillance. 17/21 (81%) infection control teams answered the survey, of which 11 (65%) believed Websök could help with infection control plans. Websök is a low-resource, easily replicable system that detects the norovirus season as reliably as laboratory data, but earlier. Using Websök in routine surveillance can help infection control teams prepare for the yearly norovirus season. PMID:24955857

Predicting user click behaviour in search engine advertisements

NASA Astrophysics Data System (ADS)

Daryaie Zanjani, Mohammad; Khadivi, Shahram

2015-10-01

According to the specific requirements and interests of users, search engines select and display advertisements that match user needs and have higher probability of attracting users' attention based on their previous search history. New objects such as user, advertisement or query cause a deterioration of precision in targeted advertising due to their lack of history. This article surveys this challenge. In the case of new objects, we first extract similar observed objects to the new object and then we use their history as the history of new object. Similarity between objects is measured based on correlation, which is a relation between user and advertisement when the advertisement is displayed to the user. This method is used for all objects, so it has helped us to accurately select relevant advertisements for users' queries. In our proposed model, we assume that similar users behave in a similar manner. We find that users with few queries are similar to new users. We will show that correlation between users and advertisements' keywords is high. Thus, users who pay attention to advertisements' keywords, click similar advertisements. In addition, users who pay attention to specific brand names might have similar behaviours too.

Detecting the norovirus season in Sweden using search engine data--meeting the needs of hospital infection control teams.

PubMed

Edelstein, Michael; Wallensten, Anders; Zetterqvist, Inga; Hulth, Anette

2014-01-01

Norovirus outbreaks severely disrupt healthcare systems. We evaluated whether Websök, an internet-based surveillance system using search engine data, improved norovirus surveillance and response in Sweden. We compared Websök users' characteristics with the general population, cross-correlated weekly Websök searches with laboratory notifications between 2006 and 2013, compared the time Websök and laboratory data crossed the epidemic threshold and surveyed infection control teams about their perception and use of Websök. Users of Websök were not representative of the general population. Websök correlated with laboratory data (b = 0.88-0.89) and gave an earlier signal to the onset of the norovirus season compared with laboratory-based surveillance. 17/21 (81%) infection control teams answered the survey, of which 11 (65%) believed Websök could help with infection control plans. Websök is a low-resource, easily replicable system that detects the norovirus season as reliably as laboratory data, but earlier. Using Websök in routine surveillance can help infection control teams prepare for the yearly norovirus season.

CBB Portal @ PNNL

Science.gov Websites

Search PNNL Home About Research Publications Jobs News Contacts Computational Biology and Bioinformatics , and engineering to transform the data into knowledge. This new quantitative, predictive biology is to empirical modeling and physics-based simulations. CBB research seeks to: Understand. Understanding

Finding Business Information on the "Invisible Web": Search Utilities vs. Conventional Search Engines.

ERIC Educational Resources Information Center

Darrah, Brenda

Researchers for small businesses, which may have no access to expensive databases or market research reports, must often rely on information found on the Internet, which can be difficult to find. Although current conventional Internet search engines are now able to index over on billion documents, there are many more documents existing in…

Is It "Writing on Water" or "Strike It Rich?" The Experiences of Prospective Teachers in Using Search Engines

ERIC Educational Resources Information Center

Sahin, Abdurrahman; Cermik, Hulya; Dogan, Birsen

2010-01-01

Information searching skills have become increasingly important for prospective teachers with the exponential growth of learning materials on the web. This study is an attempt to understand the experiences of prospective teachers with search engines through metaphoric images and to further investigate whether their experiences are related to the…

Metadata Effectiveness in Internet Discovery: An Analysis of Digital Collection Metadata Elements and Internet Search Engine Keywords

ERIC Educational Resources Information Center

Yang, Le

2016-01-01

This study analyzed digital item metadata and keywords from Internet search engines to learn what metadata elements actually facilitate discovery of digital collections through Internet keyword searching and how significantly each metadata element affects the discovery of items in a digital repository. The study found that keywords from Internet…

WaterlooClarke: TREC 2015 Clinical Decision Support Track

DTIC Science & Technology

2015-11-20

questions (diagnosis, test and treatment articles). The two different full-text search engines we adopted in order to search over the collection of articles...two different search engines using reciprocal rank fusion. The evaluation of the submitted runs using partially marked results of Text Retrieval Conference (TREC) from the previous year shows that the methodologies are promising.

Impact of Internet Search Engines on OPAC Users: A Study of Punjabi University, Patiala (India)

ERIC Educational Resources Information Center

Kumar, Shiv

2012-01-01

Purpose: The aim of this paper is to study the impact of internet search engine usage with special reference to OPAC searches in the Punjabi University Library, Patiala, Punjab (India). Design/methodology/approach: The primary data were collected from 352 users comprising faculty, research scholars and postgraduate students of the university. A…

With News Search Engines

ERIC Educational Resources Information Center

Gunn, Holly

2005-01-01

Although there are many news search engines on the Web, finding the news items one wants can be challenging. Choosing appropriate search terms is one of the biggest challenges. Unless one has seen the article that one is seeking, it is often difficult to select words that were used in the headline or text of the article. The limited archives of…

VLF P-Static Noise Reduction In Aircraft. Volume I. Current Knowledge.

DTIC Science & Technology

1980-09-01

Probe Mounted on DC-3 N7AP with Protective Cover Removed. A companion unit is mounted on the underside of the aircraft. -19- 1I b. Dayton-Aircraft...NTIS/PS-78/0532 and NTIS/PS-77/0337. For the companion Published Search of the NTIS Data Base, see NTIS/PS-79/0523. F1381 D2 NTIS/PS-79/0523/5ST Loran...79 152p Supersedes NTIS/P -78/0531 and NTIS/PS-77/0336. For the companion Published Search of the Engineering Index Data Base. see NTIS/PS-79/0524

Automated Semantic Indexing of Figure Captions to Improve Radiology Image Retrieval

PubMed Central

Kahn, Charles E.; Rubin, Daniel L.

2009-01-01

Objective We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals. Design The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. Measurements Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine. Results Estimated precision was 0.897 (95% confidence interval, 0.857–0.937). Estimated recall was 0.930 (95% confidence interval, 0.838–1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone. Conclusion Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval. PMID:19261938

Concept Based Tie-breaking and Maximal Marginal Relevance Retrieval in Microblog Retrieval

DTIC Science & Technology

2014-11-01

the same score, another singal will be used to rank these documents to break the ties , but the relative orders of other documents against these...documents remain the same. The tie- breaking step above is repeatedly applied to further break ties until all candidate signals are applied and the ranking...searched it on the Yahoo! search engine, which returned some query sug- gestions for the query. The original queries as well as their query suggestions

A study of medical and health queries to web search engines.

PubMed

Spink, Amanda; Yang, Yin; Jansen, Jim; Nykanen, Pirrko; Lorence, Daniel P; Ozmutlu, Seda; Ozmutlu, H Cenk

2004-03-01

This paper reports findings from an analysis of medical or health queries to different web search engines. We report results: (i). comparing samples of 10000 web queries taken randomly from 1.2 million query logs from the AlltheWeb.com and Excite.com commercial web search engines in 2001 for medical or health queries, (ii). comparing the 2001 findings from Excite and AlltheWeb.com users with results from a previous analysis of medical and health related queries from the Excite Web search engine for 1997 and 1999, and (iii). medical or health advice-seeking queries beginning with the word 'should'. Findings suggest: (i). a small percentage of web queries are medical or health related, (ii). the top five categories of medical or health queries were: general health, weight issues, reproductive health and puberty, pregnancy/obstetrics, and human relationships, and (iii). over time, the medical and health queries may have declined as a proportion of all web queries, as the use of specialized medical/health websites and e-commerce-related queries has increased. Findings provide insights into medical and health-related web querying and suggests some implications for the use of the general web search engines when seeking medical/health information.

Bat-Inspired Algorithm Based Query Expansion for Medical Web Information Retrieval.

PubMed

Khennak, Ilyes; Drias, Habiba

2017-02-01

With the increasing amount of medical data available on the Web, looking for health information has become one of the most widely searched topics on the Internet. Patients and people of several backgrounds are now using Web search engines to acquire medical information, including information about a specific disease, medical treatment or professional advice. Nonetheless, due to a lack of medical knowledge, many laypeople have difficulties in forming appropriate queries to articulate their inquiries, which deem their search queries to be imprecise due the use of unclear keywords. The use of these ambiguous and vague queries to describe the patients' needs has resulted in a failure of Web search engines to retrieve accurate and relevant information. One of the most natural and promising method to overcome this drawback is Query Expansion. In this paper, an original approach based on Bat Algorithm is proposed to improve the retrieval effectiveness of query expansion in medical field. In contrast to the existing literature, the proposed approach uses Bat Algorithm to find the best expanded query among a set of expanded query candidates, while maintaining low computational complexity. Moreover, this new approach allows the determination of the length of the expanded query empirically. Numerical results on MEDLINE, the on-line medical information database, show that the proposed approach is more effective and efficient compared to the baseline.

Variable neighborhood search for reverse engineering of gene regulatory networks.

PubMed

Nicholson, Charles; Goodwin, Leslie; Clark, Corey

2017-01-01

A new search heuristic, Divided Neighborhood Exploration Search, designed to be used with inference algorithms such as Bayesian networks to improve on the reverse engineering of gene regulatory networks is presented. The approach systematically moves through the search space to find topologies representative of gene regulatory networks that are more likely to explain microarray data. In empirical testing it is demonstrated that the novel method is superior to the widely employed greedy search techniques in both the quality of the inferred networks and computational time. Copyright © 2016 Elsevier Inc. All rights reserved.

How to Find Reliable ENT Info

MedlinePlus

... information about your condition may be difficult. Most search engines and directories do not rank information from your ... wants you to buy its product paid the search engine company to list it near the top. Your ...

Building a better search engine for earth science data

NASA Astrophysics Data System (ADS)

Armstrong, E. M.; Yang, C. P.; Moroni, D. F.; McGibbney, L. J.; Jiang, Y.; Huang, T.; Greguska, F. R., III; Li, Y.; Finch, C. J.

2017-12-01

Free text data searching of earth science datasets has been implemented with varying degrees of success and completeness across the spectrum of the 12 NASA earth sciences data centers. At the JPL Physical Oceanography Distributed Active Archive Center (PO.DAAC) the search engine has been developed around the Solr/Lucene platform. Others have chosen other popular enterprise search platforms like Elasticsearch. Regardless, the default implementations of these search engines leveraging factors such as dataset popularity, term frequency and inverse document term frequency do not fully meet the needs of precise relevancy and ranking of earth science search results. For the PO.DAAC, this shortcoming has been identified for several years by its external User Working Group that has assigned several recommendations to improve the relevancy and discoverability of datasets related to remotely sensed sea surface temperature, ocean wind, waves, salinity, height and gravity that comprise a total count of over 500 public availability datasets. Recently, the PO.DAAC has teamed with an effort led by George Mason University to improve the improve the search and relevancy ranking of oceanographic data via a simple search interface and powerful backend services called MUDROD (Mining and Utilizing Dataset Relevancy from Oceanographic Datasets to Improve Data Discovery) funded by the NASA AIST program. MUDROD has mined and utilized the combination of PO.DAAC earth science dataset metadata, usage metrics, and user feedback and search history to objectively extract relevance for improved data discovery and access. In addition to improved dataset relevance and ranking, the MUDROD search engine also returns recommendations to related datasets and related user queries. This presentation will report on use cases that drove the architecture and development, and the success metrics and improvements on search precision and recall that MUDROD has demonstrated over the existing PO.DAAC search interfaces.

A Forensic Examination of Online Search Facility URL Record Structures.

PubMed

Horsman, Graeme

2018-05-29

The use of search engines and associated search functions to locate content online is now common practice. As a result, a forensic examination of a suspect's online search activity can be a critical aspect in establishing whether an offense has been committed in many investigations. This article offers an analysis of online search URL structures to support law enforcement and associated digital forensics practitioners interpret acts of online searching during an investigation. Google, Bing, Yahoo!, and DuckDuckGo searching functions are examined, and key URL attribute structures and metadata have been documented. In addition, an overview of social media searching covering Twitter, Facebook, Instagram, and YouTube is offered. Results show the ability to extract embedded metadata from search engine URLs which can establish online searching behaviors and the timing of searches. © 2018 American Academy of Forensic Sciences.

The future of bibliographic standards in a networked information environment

NASA Technical Reports Server (NTRS)

1997-01-01

The main mission of the CENDI Cataloging Working Group is to provide guidelines for cataloging practices that support the sharing of database records among the CENDI agencies, and that incorporate principles based on cost effectiveness and efficiency. Recent efforts include the extension of COSATI Guidelines for the Cataloging of Technical Reports to include non-print materials, and the mapping of each agency's export file structure to USMARC. Of primary importance is the impact of electronic documents and the distributed nature of the networked information environment. Topics discussed during the workshop include the following: Trade-offs in Cataloging and Indexing Internet Information; The Impact on Current and Future Standards; A Look at WWW Metadata Initiatives; Standards for Electronic Journals; The Present and Future Search Engines; The Roles for Text Analysis Software; Advanced Search Engine Meets Metathesaurus; Locator Schemes for Internet Resources; Identifying and Cataloging Web Document Types; In Search of a New Bibliographic Record. The videos in this set include viewgraphs of charts and related materials of the workshop.

Tissue engineering of urinary bladder - current state of art and future perspectives.

PubMed

Adamowicz, Jan; Kowalczyk, Tomasz; Drewa, Tomasz

2013-01-01

Tissue engineering and biomaterials science currently offer the technology needed to replace the urinary tract wall. This review addresses current achievements and barriers for the regeneration of the urinary blad- der based on tissue engineering methods. Medline was search for urinary bladder tissue engineering regenerative medicine and stem cells. Numerous studies to develop a substitute for the native urinary bladder wall us- ing the tissue engineering approach are ongoing. Stem cells combined with biomaterials open new treatment methods, including even de novo urinary bladder construction. However, there are still many issues before advances in tissue engineering can be introduced for clinical application. Before tissue engineering techniques could be recognize as effective and safe for patients, more research stud- ies performed on large animal models and with long follow-up are needed to carry on in the future.

Factors of airplane engine performance

NASA Technical Reports Server (NTRS)

Gage, Victor R

1921-01-01

This report is based upon an analysis of a large number of airplane-engine tests. It contains the results of a search for fundamental relations between many variables of engine operation. The data used came from over 100 groups of tests made upon several engines, primarily for military information. The types of engines were the Liberty 12 and three models of the Hispano-Suiza. The tests were made in the altitude chamber, where conditions simulated altitudes up to about 30,000 feet, with engine speeds ranging from 1,200 to 2,200 r.p.m. The compression ratios of the different engines ranged from under 5 to over 8 to 1. The data taken on the tests were exceptionally complete, including variations of pressure and temperature, besides the brake and friction torques, rates of fuel and air consumption, the jacket and exhaust heat losses.

Understanding Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning.

PubMed

Nguyen, A; Yosinski, J; Clune, J

2016-01-01

The Achilles Heel of stochastic optimization algorithms is getting trapped on local optima. Novelty Search mitigates this problem by encouraging exploration in all interesting directions by replacing the performance objective with a reward for novel behaviors. This reward for novel behaviors has traditionally required a human-crafted, behavioral distance function. While Novelty Search is a major conceptual breakthrough and outperforms traditional stochastic optimization on certain problems, it is not clear how to apply it to challenging, high-dimensional problems where specifying a useful behavioral distance function is difficult. For example, in the space of images, how do you encourage novelty to produce hawks and heroes instead of endless pixel static? Here we propose a new algorithm, the Innovation Engine, that builds on Novelty Search by replacing the human-crafted behavioral distance with a Deep Neural Network (DNN) that can recognize interesting differences between phenotypes. The key insight is that DNNs can recognize similarities and differences between phenotypes at an abstract level, wherein novelty means interesting novelty. For example, a DNN-based novelty search in the image space does not explore in the low-level pixel space, but instead creates a pressure to create new types of images (e.g., churches, mosques, obelisks, etc.). Here, we describe the long-term vision for the Innovation Engine algorithm, which involves many technical challenges that remain to be solved. We then implement a simplified version of the algorithm that enables us to explore some of the algorithm's key motivations. Our initial results, in the domain of images, suggest that Innovation Engines could ultimately automate the production of endless streams of interesting solutions in any domain: for example, producing intelligent software, robot controllers, optimized physical components, and art.

The quality of patient-orientated Internet information on oral lichen planus: a pilot study.

PubMed

López-Jornet, Pía; Camacho-Alonso, Fabio

2010-10-01

This study examines the accessibility and quality Web pages related with oral lichen planus. Sites were identified using two search engines (Google and Yahoo!) and the search terms 'oral lichen planus' and 'oral lesion lichenoid'. The first 100 sites in each search were visited and classified. The web sites were evaluated for content quality by using the validated DISCERN rating instrument. JAMA benchmarks and 'Health on the Net' seal (HON). A total of 109,000 sites were recorded in Google using the search terms and 520,000 in Yahoo! A total of 19 Web pages considered relevant were examined on Google and 20 on Yahoo! As regards the JAMA benchmarks, only two pages satisfied the four criteria in Google (10%), and only three (15%) in Yahoo! As regards DISCERN, the overall quality of web site information was poor, no site reaching the maximum score. In Google 78.94% of sites had important deficiencies, and 50% in Yahoo!, the difference between the two search engines being statistically significant (P = 0.031). Only five pages (17.2%) on Google and eight (40%) on Yahoo! showed the HON code. Based on our review, doctors must assume primary responsibility for educating and counselling their patients. © 2010 Blackwell Publishing Ltd.

Our Commitment to Reliable Health and Medical Information

MedlinePlus

... 000 visitors world-wide per day. HONcode Toolbar: search engine and checker of the certification status Automatically checks ... HONcode status when browsing health web sites. The search engine indexes only HONcode-certified sites. HONcodeHunt currently includes ...

Information Clustering Based on Fuzzy Multisets.

ERIC Educational Resources Information Center

Miyamoto, Sadaaki

2003-01-01

Proposes a fuzzy multiset model for information clustering with application to information retrieval on the World Wide Web. Highlights include search engines; term clustering; document clustering; algorithms for calculating cluster centers; theoretical properties concerning clustering algorithms; and examples to show how the algorithms work.…

Telecommunications and data acquisition

NASA Technical Reports Server (NTRS)

Renzetti, N. A. (Editor)

1981-01-01

Deep Space Network progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations is reported. In addition, developments in Earth based radio technology as applied to geodynamics, astrophysics, and the radio search for extraterrestrial intelligence are reported.

Using the Internet in Career Education. Practice Application Brief No. 1.

ERIC Educational Resources Information Center

Wagner, Judith O.

The World Wide Web has a wealth of information on career planning, individual jobs, and job search methods that counselors and teachers can use. Search engines such as Yahoo! and Magellan, organized like library tools, and engines such as AltaVista and HotBot search words or phrases. Web indexes offer a variety of features. The criteria for…

Full Text and Figure Display Improves Bioscience Literature Search

PubMed Central

Divoli, Anna; Wooldridge, Michael A.; Hearst, Marti A.

2010-01-01

When reading bioscience journal articles, many researchers focus attention on the figures and their captions. This observation led to the development of the BioText literature search engine [1], a freely available Web-based application that allows biologists to search over the contents of Open Access Journals, and see figures from the articles displayed directly in the search results. This article presents a qualitative assessment of this system in the form of a usability study with 20 biologist participants using and commenting on the system. 19 out of 20 participants expressed a desire to use a bioscience literature search engine that displays articles' figures alongside the full text search results. 15 out of 20 participants said they would use a caption search and figure display interface either frequently or sometimes, while 4 said rarely and 1 said undecided. 10 out of 20 participants said they would use a tool for searching the text of tables and their captions either frequently or sometimes, while 7 said they would use it rarely if at all, 2 said they would never use it, and 1 was undecided. This study found evidence, supporting results of an earlier study, that bioscience literature search systems such as PubMed should show figures from articles alongside search results. It also found evidence that full text and captions should be searched along with the article title, metadata, and abstract. Finally, for a subset of users and information needs, allowing for explicit search within captions for figures and tables is a useful function, but it is not entirely clear how to cleanly integrate this within a more general literature search interface. Such a facility supports Open Access publishing efforts, as it requires access to full text of documents and the lifting of restrictions in order to show figures in the search interface. PMID:20418942

Searching Choices: Quantifying Decision-Making Processes Using Search Engine Data.

PubMed

Moat, Helen Susannah; Olivola, Christopher Y; Chater, Nick; Preis, Tobias

2016-07-01

When making a decision, humans consider two types of information: information they have acquired through their prior experience of the world, and further information they gather to support the decision in question. Here, we present evidence that data from search engines such as Google can help us model both sources of information. We show that statistics from search engines on the frequency of content on the Internet can help us estimate the statistical structure of prior experience; and, specifically, we outline how such statistics can inform psychological theories concerning the valuation of human lives, or choices involving delayed outcomes. Turning to information gathering, we show that search query data might help measure human information gathering, and it may predict subsequent decisions. Such data enable us to compare information gathered across nations, where analyses suggest, for example, a greater focus on the future in countries with a higher per capita GDP. We conclude that search engine data constitute a valuable new resource for cognitive scientists, offering a fascinating new tool for understanding the human decision-making process. Copyright © 2016 The Authors. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Acceleration of the chemistry solver for modeling DI engine combustion using dynamic adaptive chemistry (DAC) schemes

NASA Astrophysics Data System (ADS)

Shi, Yu; Liang, Long; Ge, Hai-Wen; Reitz, Rolf D.

2010-03-01

Acceleration of the chemistry solver for engine combustion is of much interest due to the fact that in practical engine simulations extensive computational time is spent solving the fuel oxidation and emission formation chemistry. A dynamic adaptive chemistry (DAC) scheme based on a directed relation graph error propagation (DRGEP) method has been applied to study homogeneous charge compression ignition (HCCI) engine combustion with detailed chemistry (over 500 species) previously using an R-value-based breadth-first search (RBFS) algorithm, which significantly reduced computational times (by as much as 30-fold). The present paper extends the use of this on-the-fly kinetic mechanism reduction scheme to model combustion in direct-injection (DI) engines. It was found that the DAC scheme becomes less efficient when applied to DI engine simulations using a kinetic mechanism of relatively small size and the accuracy of the original DAC scheme decreases for conventional non-premixed combustion engine. The present study also focuses on determination of search-initiating species, involvement of the NOx chemistry, selection of a proper error tolerance, as well as treatment of the interaction of chemical heat release and the fuel spray. Both the DAC schemes were integrated into the ERC KIVA-3v2 code, and simulations were conducted to compare the two schemes. In general, the present DAC scheme has better efficiency and similar accuracy compared to the previous DAC scheme. The efficiency depends on the size of the chemical kinetics mechanism used and the engine operating conditions. For cases using a small n-heptane kinetic mechanism of 34 species, 30% of the computational time is saved, and 50% for a larger n-heptane kinetic mechanism of 61 species. The paper also demonstrates that by combining the present DAC scheme with an adaptive multi-grid chemistry (AMC) solver, it is feasible to simulate a direct-injection engine using a detailed n-heptane mechanism with 543 species with practical computer time.

Toward two-dimensional search engines

NASA Astrophysics Data System (ADS)

Ermann, L.; Chepelianskii, A. D.; Shepelyansky, D. L.

2012-07-01

We study the statistical properties of various directed networks using ranking of their nodes based on the dominant vectors of the Google matrix known as PageRank and CheiRank. On average PageRank orders nodes proportionally to a number of ingoing links, while CheiRank orders nodes proportionally to a number of outgoing links. In this way, the ranking of nodes becomes two dimensional which paves the way for the development of two-dimensional search engines of a new type. Statistical properties of information flow on the PageRank-CheiRank plane are analyzed for networks of British, French and Italian universities, Wikipedia, Linux Kernel, gene regulation and other networks. A special emphasis is done for British universities networks using the large database publicly available in the UK. Methods of spam links control are also analyzed.

Search 3.0: Present, Personal, Precise

NASA Astrophysics Data System (ADS)

Spivack, Nova

The next generation of Web search is already beginning to emerge. With it we will see several shifts in the way people search, and the way major search engines provide search functionality to consumers.

Mail LOG: Program operating instructions

NASA Technical Reports Server (NTRS)

Harris, D. K.

1979-01-01

The operating instructions for the software package, MAIL LOG, developed for the Scout Project Automatic Data System, SPADS, are provided. The program is written in FORTRAN for the PRIME 300 computer system. The MAIL LOG program has the following four modes of operation: (1) INPUT - putting new records into the data base (2) REVISE - changing or modifying existing records in the data base (3) SEARCH - finding special records existing in the data base (4) ARCHIVE - store or put away existing records in the data base. The output includes special printouts of records in the data base and results from the INPUT and SEARCH modes. The MAIL LOG data base consists of three main subfiles: Incoming and outgoing mail correspondence; Design Information Releases and Releases and Reports; and Drawings and Engineering orders.

An information retrieval system for computerized patient records in the context of a daily hospital practice: the example of the Léon Bérard Cancer Center (France).

PubMed

Biron, P; Metzger, M H; Pezet, C; Sebban, C; Barthuet, E; Durand, T

2014-01-01

A full-text search tool was introduced into the daily practice of Léon Bérard Center (France), a health care facility devoted to treatment of cancer. This tool was integrated into the hospital information system by the IT department having been granted full autonomy to improve the system. To describe the development and various uses of a tool for full-text search of computerized patient records. The technology is based on Solr, an open-source search engine. It is a web-based application that processes HTTP requests and returns HTTP responses. A data processing pipeline that retrieves data from different repositories, normalizes, cleans and publishes it to Solr, was integrated in the information system of the Leon Bérard center. The IT department developed also user interfaces to allow users to access the search engine within the computerized medical record of the patient. From January to May 2013, 500 queries were launched per month by an average of 140 different users. Several usages of the tool were described, as follows: medical management of patients, medical research, and improving the traceability of medical care in medical records. The sensitivity of the tool for detecting the medical records of patients diagnosed with both breast cancer and diabetes was 83.0%, and its positive predictive value was 48.7% (gold standard: manual screening by a clinical research assistant). The project demonstrates that the introduction of full-text-search tools allowed practitioners to use unstructured medical information for various purposes.

Optimizing Earth Data Search Ranking using Deep Learning and Real-time User Behaviour

NASA Astrophysics Data System (ADS)

Jiang, Y.; Yang, C. P.; Armstrong, E. M.; Huang, T.; Moroni, D. F.; McGibbney, L. J.; Greguska, F. R., III

2017-12-01

Finding Earth science data has been a challenging problem given both the quantity of data available and the heterogeneity of the data across a wide variety of domains. Current search engines in most geospatial data portals tend to induce end users to focus on one single data characteristic dimension (e.g., term frequency-inverse document frequency (TF-IDF) score, popularity, release date, etc.). This approach largely fails to take account of users' multidimensional preferences for geospatial data, and hence may likely result in a less than optimal user experience in discovering the most applicable dataset out of a vast range of available datasets. With users interacting with search engines, sufficient information is already hidden in the log files. Compared with explicit feedback data, information that can be derived/extracted from log files is virtually free and substantially more timely. In this dissertation, I propose an online deep learning framework that can quickly update the learning function based on real-time user clickstream data. The contributions of this framework include 1) a log processor that can ingest, process and create training data from web logs in a real-time manner; 2) a query understanding module to better interpret users' search intent using web log processing results and metadata; 3) a feature extractor that identifies ranking features representing users' multidimensional interests of geospatial data; and 4) a deep learning based ranking algorithm that can be trained incrementally using user behavior data. The search ranking results will be evaluated using precision at K and normalized discounted cumulative gain (NDCG).

Web-based information on the treatment of oral leukoplakia - quality and readability.

PubMed

Wiriyakijja, Paswach; Fedele, Stefano; Porter, Stephen; Ni Riordain, Richeal

2016-09-01

To categorise the content and assess the quality and readability of the online information regarding the treatment for oral leukoplakia. An online search using the term 'leukoplakia treatment' was carried out on 8th June 2015 using the Google search engine. The content, quality and readability of the first 100 sites were explored. The quality of the web information was assessed using the following tools, the DISCERN instrument and the Journal of the American Medical Association (JAMA) benchmarks for website analysis and the HON seal. Readability was assessed via the Flesch Reading Ease Score. The search strategy generated 357 000 sites on the Google search engine. Due to duplicate links, non-operating links and irrelevant links, a total of 47 of the first 100 websites were included in this study. The mean overall rating achieved by included websites using the DISCERN instrument was 2.3. With regard to the JAMA benchmarks, the vast majority of examined websites (95.7%) completely fulfilled the disclosure benchmark and less than 50% of included websites met the three remaining criteria. A mean total readability score of 47.5 was recorded with almost 90% of websites having a readability level ranging from fairly difficult to very difficult. Based on this study, the online health information regarding oral leukoplakia has challenging readability with content of questionable accuracy. As patients often search for health information online, it would be prudent for clinicians to highlight the caution with which online information should be interpreted. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Seasonal trends in sleep-disordered breathing: evidence from Internet search engine query data.

PubMed

Ingram, David G; Matthews, Camilla K; Plante, David T

2015-03-01

The primary aim of the current study was to test the hypothesis that there is a seasonal component to snoring and obstructive sleep apnea (OSA) through the use of Google search engine query data. Internet search engine query data were retrieved from Google Trends from January 2006 to December 2012. Monthly normalized search volume was obtained over that 7-year period in the USA and Australia for the following search terms: "snoring" and "sleep apnea". Seasonal effects were investigated by fitting cosinor regression models. In addition, the search terms "snoring children" and "sleep apnea children" were evaluated to examine seasonal effects in pediatric populations. Statistically significant seasonal effects were found using cosinor analysis in both USA and Australia for "snoring" (p < 0.00001 for both countries). Similarly, seasonal patterns were observed for "sleep apnea" in the USA (p = 0.001); however, cosinor analysis was not significant for this search term in Australia (p = 0.13). Seasonal patterns for "snoring children" and "sleep apnea children" were observed in the USA (p = 0.002 and p < 0.00001, respectively), with insufficient search volume to examine these search terms in Australia. All searches peaked in the winter or early spring in both countries, with the magnitude of seasonal effect ranging from 5 to 50 %. Our findings indicate that there are significant seasonal trends for both snoring and sleep apnea internet search engine queries, with a peak in the winter and early spring. Further research is indicated to determine the mechanisms underlying these findings, whether they have clinical impact, and if they are associated with other comorbid medical conditions that have similar patterns of seasonal exacerbation.

From the Director: Surfing the Web for Health Information

MedlinePlus

... Reliable Results Most Internet users first visit a search engine — like Google or Yahoo! — when seeking health information. ... medical terms like "cancer" or "diabetes" into a search engine, the top-ten results will likely include authoritative ...

An approach to development of ontological knowledge base in the field of scientific and research activity in Russia

NASA Astrophysics Data System (ADS)

Murtazina, M. Sh; Avdeenko, T. V.

2018-05-01

The state of art and the progress in application of semantic technologies in the field of scientific and research activity have been analyzed. Even elementary empirical comparison has shown that the semantic search engines are superior in all respects to conventional search technologies. However, semantic information technologies are insufficiently used in the field of scientific and research activity in Russia. In present paper an approach to construction of ontological model of knowledge base is proposed. The ontological model is based on the upper-level ontology and the RDF mechanism for linking several domain ontologies. The ontological model is implemented in the Protégé environment.

Boolean logic tree of graphene-based chemical system for molecular computation and intelligent molecular search query.

PubMed

Huang, Wei Tao; Luo, Hong Qun; Li, Nian Bing

2014-05-06

The most serious, and yet unsolved, problem of constructing molecular computing devices consists in connecting all of these molecular events into a usable device. This report demonstrates the use of Boolean logic tree for analyzing the chemical event network based on graphene, organic dye, thrombin aptamer, and Fenton reaction, organizing and connecting these basic chemical events. And this chemical event network can be utilized to implement fluorescent combinatorial logic (including basic logic gates and complex integrated logic circuits) and fuzzy logic computing. On the basis of the Boolean logic tree analysis and logic computing, these basic chemical events can be considered as programmable "words" and chemical interactions as "syntax" logic rules to construct molecular search engine for performing intelligent molecular search query. Our approach is helpful in developing the advanced logic program based on molecules for application in biosensing, nanotechnology, and drug delivery.

Arc-An OAI Service Provider for Digital Library Federation; Kepler-An OAI Data/Service Provider for the Individual; Information Objects and Rights Management: A Mediation-Based Approach to DRM Interoperability; Automated Name Authority Control and Enhanced Searching in the Levy Collection; Renardus Project Developments and the Wider Digital Library Context.

ERIC Educational Resources Information Center

Liu, Xiaoming; Maly, Kurt; Zubair, Mohammad; Nelson, Michael L.; Erickson, John S.; DiLauro, Tim; Choudhury, G. Sayeed; Patton, Mark; Warner, James W.; Brown, Elizabeth W.; Heery, Rachel; Carpenter, Leona; Day, Michael

2001-01-01

Includes five articles that discuss the OAI (Open Archive Initiative), an interface between data providers and service providers; information objects and digital rights management interoperability; digitizing library collections, including automated name authority control, metadata, and text searching engines; and building digital library services…

Speeding up the screening of steroids in urine: development of a user-friendly library.

PubMed

Galesio, M; López-Fdez, H; Reboiro-Jato, M; Gómez-Meire, Silvana; Glez-Peña, D; Fdez-Riverola, F; Lodeiro, Carlos; Diniz, M E; Capelo, J L

2013-12-11

This work presents a novel database search engine - MLibrary - designed to assist the user in the detection and identification of androgenic anabolic steroids (AAS) and its metabolites by matrix assisted laser desorption/ionization (MALDI) and mass spectrometry-based strategies. The detection of the AAS in the samples was accomplished by searching (i) the mass spectrometric (MS) spectra against the library developed to identify possible positives and (ii) by comparison of the tandem mass spectrometric (MS/MS) spectra produced after fragmentation of the possible positives with a complete set of spectra that have previously been assigned to the software. The urinary screening for anabolic agents plays a major role in anti-doping laboratories as they represent the most abused drug class in sports. With the help of the MLibrary software application, the use of MALDI techniques for doping control is simplified and the time for evaluation and interpretation of the results is reduced. To do so, the search engine takes as input several MALDI-TOF-MS and MALDI-TOF-MS/MS spectra. It aids the researcher in an automatic mode by identifying possible positives in a single MS analysis and then confirming their presence in tandem MS analysis by comparing the experimental tandem mass spectrometric data with the database. Furthermore, the search engine can, potentially, be further expanded to other compounds in addition to AASs. The applicability of the MLibrary tool is shown through the analysis of spiked urine samples. Copyright © 2013 Elsevier Inc. All rights reserved.

Evidential significance of automotive paint trace evidence using a pattern recognition based infrared library search engine for the Paint Data Query Forensic Database.

PubMed

Lavine, Barry K; White, Collin G; Allen, Matthew D; Fasasi, Ayuba; Weakley, Andrew

2016-10-01

A prototype library search engine has been further developed to search the infrared spectral libraries of the paint data query database to identify the line and model of a vehicle from the clear coat, surfacer-primer, and e-coat layers of an intact paint chip. For this study, search prefilters were developed from 1181 automotive paint systems spanning 3 manufacturers: General Motors, Chrysler, and Ford. The best match between each unknown and the spectra in the hit list generated by the search prefilters was identified using a cross-correlation library search algorithm that performed both a forward and backward search. In the forward search, spectra were divided into intervals and further subdivided into windows (which corresponds to the time lag for the comparison) within those intervals. The top five hits identified in each search window were compiled; a histogram was computed that summarized the frequency of occurrence for each library sample, with the IR spectra most similar to the unknown flagged. The backward search computed the frequency and occurrence of each line and model without regard to the identity of the individual spectra. Only those lines and models with a frequency of occurrence greater than or equal to 20% were included in the final hit list. If there was agreement between the forward and backward search results, the specific line and model common to both hit lists was always the correct assignment. Samples assigned to the same line and model by both searches are always well represented in the library and correlate well on an individual basis to specific library samples. For these samples, one can have confidence in the accuracy of the match. This was not the case for the results obtained using commercial library search algorithms, as the hit quality index scores for the top twenty hits were always greater than 99%. Copyright © 2016 Elsevier B.V. All rights reserved.

The telecommunications and data acquisition report

NASA Technical Reports Server (NTRS)

Renzetti, N. A.

1980-01-01

Deep Space Network progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implemention, and operations is documented. In addition, developments in Earth based radio technology as applied to geodynamics, astrophysics, and the radio search for extraterrestrial intelligence are reported.

Metadata: Pure and Simple, or Is It?

ERIC Educational Resources Information Center

Chalmers, Marilyn

2002-01-01

Discusses issues concerning metadata in Web pages based on experiences in a vocational education center library in Queensland (Australia). Highlights include Dublin Core elements; search engines; controlled vocabulary; performance measurement to assess usage patterns and provide quality control over the vocabulary; and considerations given the…

BJUT at TREC 2015 Microblog Track: Real Time Filtering Using Knowledge Base

DTIC Science & Technology

2015-11-20

learning to rank of tweets. In Proceedings of the 23rd International Conference on Computational Linguistics , pages 295–303. Association for Computational... Linguistics , 2010. Thorsten Joachims. Optimizing search engines using clickthrough data. In Proceedings of the eighth ACM SIGKDD international

The Telecommunications and Data Acquisition Report

NASA Technical Reports Server (NTRS)

Posner, E. C. (Editor)

1986-01-01

Deep Space Network progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations is documented. In addition, developments in Earth-based radio technology as applied to geodynamics, astrophysics and the radio search for extraterrestrial intelligence are reported.

Maintaining Academic Integrity in On-Line Education.

ERIC Educational Resources Information Center

Heberling, Michael

2002-01-01

Discussion of academic cheating and plagiarism focuses on occurrences in online courses, based on experiences at Baker College (Michigan). Highlights include tools to fight plagiarism; using search engines to detect plagiarism; digital paper mills; plagiarism detection companies; and the role of administrators and faculty. (LRW)

Development of a PubMed Based Search Tool for Identifying Sex and Gender Specific Health Literature.

PubMed

Song, Michael M; Simonsen, Cheryl K; Wilson, Joanna D; Jenkins, Marjorie R

2016-02-01

An effective literature search strategy is critical to achieving the aims of Sex and Gender Specific Health (SGSH): to understand sex and gender differences through research and to effectively incorporate the new knowledge into the clinical decision making process to benefit both male and female patients. The goal of this project was to develop and validate an SGSH literature search tool that is readily and freely available to clinical researchers and practitioners. PubMed, a freely available search engine for the Medline database, was selected as the platform to build the SGSH literature search tool. Combinations of Medical Subject Heading terms, text words, and title words were evaluated for optimal specificity and sensitivity. The search tool was then validated against reference bases compiled for two disease states, diabetes and stroke. Key sex and gender terms and limits were bundled to create a search tool to facilitate PubMed SGSH literature searches. During validation, the search tool retrieved 50 of 94 (53.2%) stroke and 62 of 95 (65.3%) diabetes reference articles selected for validation. A general keyword search of stroke or diabetes combined with sex difference retrieved 33 of 94 (35.1%) stroke and 22 of 95 (23.2%) diabetes reference base articles, with lower sensitivity and specificity for SGSH content. The Texas Tech University Health Sciences Center SGSH PubMed Search Tool provides higher sensitivity and specificity to sex and gender specific health literature. The tool will facilitate research, clinical decision-making, and guideline development relevant to SGSH.

Development of a PubMed Based Search Tool for Identifying Sex and Gender Specific Health Literature

PubMed Central

Song, Michael M.; Simonsen, Cheryl K.; Wilson, Joanna D.

2016-01-01

Abstract Background: An effective literature search strategy is critical to achieving the aims of Sex and Gender Specific Health (SGSH): to understand sex and gender differences through research and to effectively incorporate the new knowledge into the clinical decision making process to benefit both male and female patients. The goal of this project was to develop and validate an SGSH literature search tool that is readily and freely available to clinical researchers and practitioners. Methods: PubMed, a freely available search engine for the Medline database, was selected as the platform to build the SGSH literature search tool. Combinations of Medical Subject Heading terms, text words, and title words were evaluated for optimal specificity and sensitivity. The search tool was then validated against reference bases compiled for two disease states, diabetes and stroke. Results: Key sex and gender terms and limits were bundled to create a search tool to facilitate PubMed SGSH literature searches. During validation, the search tool retrieved 50 of 94 (53.2%) stroke and 62 of 95 (65.3%) diabetes reference articles selected for validation. A general keyword search of stroke or diabetes combined with sex difference retrieved 33 of 94 (35.1%) stroke and 22 of 95 (23.2%) diabetes reference base articles, with lower sensitivity and specificity for SGSH content. Conclusions: The Texas Tech University Health Sciences Center SGSH PubMed Search Tool provides higher sensitivity and specificity to sex and gender specific health literature. The tool will facilitate research, clinical decision-making, and guideline development relevant to SGSH. PMID:26555409

Modified Backtracking Search Optimization Algorithm Inspired by Simulated Annealing for Constrained Engineering Optimization Problems

PubMed Central

Wang, Hailong; Sun, Yuqiu; Su, Qinghua; Xia, Xuewen

2018-01-01

The backtracking search optimization algorithm (BSA) is a population-based evolutionary algorithm for numerical optimization problems. BSA has a powerful global exploration capacity while its local exploitation capability is relatively poor. This affects the convergence speed of the algorithm. In this paper, we propose a modified BSA inspired by simulated annealing (BSAISA) to overcome the deficiency of BSA. In the BSAISA, the amplitude control factor (F) is modified based on the Metropolis criterion in simulated annealing. The redesigned F could be adaptively decreased as the number of iterations increases and it does not introduce extra parameters. A self-adaptive ε-constrained method is used to handle the strict constraints. We compared the performance of the proposed BSAISA with BSA and other well-known algorithms when solving thirteen constrained benchmarks and five engineering design problems. The simulation results demonstrated that BSAISA is more effective than BSA and more competitive with other well-known algorithms in terms of convergence speed. PMID:29666635

Effectiveness of off-line and web-based promotion of health information web sites.

PubMed

Jones, Craig E; Pinnock, Carole B

2002-01-01

The relative effectiveness of off-line and web-based promotional activities in increasing the use of health information web sites by target audiences were compared. Visitor sessions were classified according to their method of arrival at the site (referral) as external web site, search engine, or "no referrer" (i.e., visitor arriving at the site by inputting URL or using bookmarks). The number of Australian visitor sessions correlated with no referrer referrals but not web site or search-engine referrals. Results showed that the targeted consumer group is more likely to access the web site as a result of off-line promotional activities. The properties of target audiences likely to influence the effectiveness of off-line versus on-line promotional strategies include the size of the Internet using population of the target audience, their proficiency in the use of the Internet, and the increase in effectiveness of off-line promotional activities when applied to locally defined target audiences.

Monitoring hand, foot and mouth disease by combining search engine query data and meteorological factors.

PubMed

Huang, Da-Cang; Wang, Jin-Feng

2018-01-15

Hand, foot and mouth disease (HFMD) has been recognized as a significant public health threat and poses a tremendous challenge to disease control departments. To date, the relationship between meteorological factors and HFMD has been documented, and public interest of disease has been proven to be trackable from the Internet. However, no study has explored the combination of these two factors in the monitoring of HFMD. Therefore, the main aim of this study was to develop an effective monitoring model of HFMD in Guangzhou, China by utilizing historical HFMD cases, Internet-based search engine query data and meteorological factors. To this end, a case study was conducted in Guangzhou, using a network-based generalized additive model (GAM) including all factors related to HFMD. Three other models were also constructed using some of the variables for comparison. The results suggested that the model showed the best estimating ability when considering all of the related factors. Copyright © 2017 Elsevier B.V. All rights reserved.

pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning.

PubMed

Zhou, Xie-Xuan; Zeng, Wen-Feng; Chi, Hao; Luo, Chunjie; Liu, Chao; Zhan, Jianfeng; He, Si-Min; Zhang, Zhifei

2017-12-05

In tandem mass spectrometry (MS/MS)-based proteomics, search engines rely on comparison between an experimental MS/MS spectrum and the theoretical spectra of the candidate peptides. Hence, accurate prediction of the theoretical spectra of peptides appears to be particularly important. Here, we present pDeep, a deep neural network-based model for the spectrum prediction of peptides. Using the bidirectional long short-term memory (BiLSTM), pDeep can predict higher-energy collisional dissociation, electron-transfer dissociation, and electron-transfer and higher-energy collision dissociation MS/MS spectra of peptides with >0.9 median Pearson correlation coefficients. Further, we showed that intermediate layer of the neural network could reveal physicochemical properties of amino acids, for example the similarities of fragmentation behaviors between amino acids. We also showed the potential of pDeep to distinguish extremely similar peptides (peptides that contain isobaric amino acids, for example, GG = N, AG = Q, or even I = L), which were very difficult to distinguish using traditional search engines.