Semantic concept-enriched dependence model for medical information retrieval.

PubMed

Choi, Sungbin; Choi, Jinwook; Yoo, Sooyoung; Kim, Heechun; Lee, Youngho

2014-02-01

In medical information retrieval research, semantic resources have been mostly used by expanding the original query terms or estimating the concept importance weight. However, implicit term-dependency information contained in semantic concept terms has been overlooked or at least underused in most previous studies. In this study, we incorporate a semantic concept-based term-dependence feature into a formal retrieval model to improve its ranking performance. Standardized medical concept terms used by medical professionals were assumed to have implicit dependency within the same concept. We hypothesized that, by elaborately revising the ranking algorithms to favor documents that preserve those implicit dependencies, the ranking performance could be improved. The implicit dependence features are harvested from the original query using MetaMap. These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM). We designed four different variants of the model, with each variant having distinct characteristics in the feature formulation method. We performed leave-one-out cross validations on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OHSUMED), which are representative test collections in medical information retrieval research. Our semantic concept-enriched dependence model consistently outperformed other state-of-the-art retrieval methods. Analysis shows that the performance gain has occurred independently of the concept's explicit importance in the query. By capturing implicit knowledge with regard to the query term relationships and incorporating them into a ranking model, we could build a more robust and effective retrieval model, independent of the concept importance. Copyright © 2013 Elsevier Inc. All rights reserved.

Activation of semantic information at the sublexical level during handwriting production: Evidence from inhibition effects of Chinese semantic radicals in the picture-word interference paradigm.

PubMed

Chen, Xuqian; Liao, Yuanlan; Chen, Xianzhe

2017-08-01

Using a non-alphabetic language (e.g., Chinese), the present study tested a novel view that semantic information at the sublexical level should be activated during handwriting production. Over 80% of Chinese characters are phonograms, in which semantic radicals represent category information (e.g., 'chair,' 'peach,' 'orange' are related to plants) while phonetic radicals represent phonetic information (e.g., 'wolf,' 'brightness,' 'male,' are all pronounced /lang/). Under different semantic category conditions at the lexical level (semantically related in Experiment 1; semantically unrelated in Experiment 2), the orthographic relatedness and semantic relatedness of semantic radicals in the picture name and its distractor were manipulated under different SOAs (i.e., stimulus onset asynchrony, the interval between the onset of the picture and the onset of the interference word). Two questions were addressed: (1) Is it possible that semantic information could be activated in the sublexical level conditions? (2) How are semantic and orthographic information dynamically accessed in word production? Results showed that both orthographic and semantic information were activated under the present picture-word interference paradigm, dynamically under different SOAs, which supported our view that discussions on semantic processes in the writing modality should be extended to the sublexical level. The current findings provide possibility for building new orthography-phonology-semantics models in writing. © 2017 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

The agent-based spatial information semantic grid

NASA Astrophysics Data System (ADS)

Cui, Wei; Zhu, YaQiong; Zhou, Yong; Li, Deren

2006-10-01

Analyzing the characteristic of multi-Agent and geographic Ontology, The concept of the Agent-based Spatial Information Semantic Grid (ASISG) is defined and the architecture of the ASISG is advanced. ASISG is composed with Multi-Agents and geographic Ontology. The Multi-Agent Systems are composed with User Agents, General Ontology Agent, Geo-Agents, Broker Agents, Resource Agents, Spatial Data Analysis Agents, Spatial Data Access Agents, Task Execution Agent and Monitor Agent. The architecture of ASISG have three layers, they are the fabric layer, the grid management layer and the application layer. The fabric layer what is composed with Data Access Agent, Resource Agent and Geo-Agent encapsulates the data of spatial information system so that exhibits a conceptual interface for the Grid management layer. The Grid management layer, which is composed with General Ontology Agent, Task Execution Agent and Monitor Agent and Data Analysis Agent, used a hybrid method to manage all resources that were registered in a General Ontology Agent that is described by a General Ontology System. The hybrid method is assembled by resource dissemination and resource discovery. The resource dissemination push resource from Local Ontology Agent to General Ontology Agent and the resource discovery pull resource from the General Ontology Agent to Local Ontology Agents. The Local Ontology Agent is derived from special domain and describes the semantic information of local GIS. The nature of the Local Ontology Agents can be filtrated to construct a virtual organization what could provides a global scheme. The virtual organization lightens the burdens of guests because they need not search information site by site manually. The application layer what is composed with User Agent, Geo-Agent and Task Execution Agent can apply a corresponding interface to a domain user. The functions that ASISG should provide are: 1) It integrates different spatial information systems on the semantic The Grid

Synergetic computer and holonics - information dynamics of a semantic computer

NASA Astrophysics Data System (ADS)

Shimizu, H.; Yamaguchi, Y.

1987-12-01

The dynamics of semantic information in biosystem is studied based on holons, generators of mutual relations. Any biosystem has an internal world, a so-called "self", which has an intrinsic purpose rendering the system continuously alive and developed as much as possible against a fluctuating external world. External signals to the system through sensory organs are classified by the self into two basic categories, semantic information with some meaning and value for the purpose and inputs from background and noise sources. Due to this breaking of semantic symmetry, any input signals are transformed into a figure and background, respectively. As a typical example, the visual perception of vertebrates is studied. For such semantic transformation the external signal is first decomposed and converted into a number of elementary signs named "syntons" which are then transmitted into a sensory area of cortex corresponding to an image synthesizer. The synthesizer is a sort of autonomic parallel processor composed of autonomic units, "holons", which are characterized by many internal modes. Syntons are fed into the holons one by one. A set of the elementary meanings, the so-called "semons", provided to the synton are encoded in the internal modes of the holon; that is, each internal mode encodes a semon. A dynamic information theory for the transformation of external signals to semantic information is developed based on our model which we call holovision. Holovision is a dynamic model of visual perception that processes an autonomic ability to self-organize visual images. Autonomous oscillators are utilized as the line processors to encode line elements with specific orientations in their phases as semons. An information space is defined according to the assembly of holons; the spatial plane on which holons are arranged is a syntactic subspace while the internal modes of the holons span a semantic subspace in the orthogonal direction. In this information space, the image of

A development framework for semantically interoperable health information systems.

PubMed

Lopez, Diego M; Blobel, Bernd G M E

2009-02-01

Semantic interoperability is a basic challenge to be met for new generations of distributed, communicating and co-operating health information systems (HIS) enabling shared care and e-Health. Analysis, design, implementation and maintenance of such systems and intrinsic architectures have to follow a unified development methodology. The Generic Component Model (GCM) is used as a framework for modeling any system to evaluate and harmonize state of the art architecture development approaches and standards for health information systems as well as to derive a coherent architecture development framework for sustainable, semantically interoperable HIS and their components. The proposed methodology is based on the Rational Unified Process (RUP), taking advantage of its flexibility to be configured for integrating other architectural approaches such as Service-Oriented Architecture (SOA), Model-Driven Architecture (MDA), ISO 10746, and HL7 Development Framework (HDF). Existing architectural approaches have been analyzed, compared and finally harmonized towards an architecture development framework for advanced health information systems. Starting with the requirements for semantic interoperability derived from paradigm changes for health information systems, and supported in formal software process engineering methods, an appropriate development framework for semantically interoperable HIS has been provided. The usability of the framework has been exemplified in a public health scenario.

E-Government Goes Semantic Web: How Administrations Can Transform Their Information Processes

NASA Astrophysics Data System (ADS)

Klischewski, Ralf; Ukena, Stefan

E-government applications and services are built mainly on access to, retrieval of, integration of, and delivery of relevant information to citizens, businesses, and administrative users. In order to perform such information processing automatically through the Semantic Web,1 machine-readable2 enhancements of web resources are needed, based on the understanding of the content and context of the information in focus. While these enhancements are far from trivial to produce, administrations in their role of information and service providers so far find little guidance on how to migrate their web resources and enable a new quality of information processing; even research is still seeking best practices. Therefore, the underlying research question of this chapter is: what are the appropriate approaches which guide administrations in transforming their information processes toward the Semantic Web? In search for answers, this chapter analyzes the challenges and possible solutions from the perspective of administrations: (a) the reconstruction of the information processing in the e-government in terms of how semantic technologies must be employed to support information provision and consumption through the Semantic Web; (b) the required contribution to the transformation is compared to the capabilities and expectations of administrations; and (c) available experience with the steps of transformation are reviewed and discussed as to what extent they can be expected to successfully drive the e-government to the Semantic Web. This research builds on studying the case of Schleswig-Holstein, Germany, where semantic technologies have been used within the frame of the Access-eGov3 project in order to semantically enhance electronic service interfaces with the aim of providing a new way of accessing and combining e-government services.

Semantic and phonological information in sentence recall: converging psycholinguistic and neuropsychological evidence.

PubMed

Schweppe, Judith; Rummer, Ralf; Bormann, Tobias; Martin, Randi C

2011-12-01

We present one experiment and a neuropsychological case study to investigate to what extent phonological and semantic representations contribute to short-term sentence recall. We modified Potter and Lombardi's (1990) intrusion paradigm, in which retention of a list interferes with sentence recall such that on the list a semantically related lure is presented, which is expected to intrude into sentence recall. In our version, lure words are either semantically related to target words in the sentence or semantically plus phonologically related. With healthy participants, intrusions are more frequent when lure and target overlap phonologically in addition to semantically than when they solely overlap semantically. When this paradigm is applied to a patient with a phonological short-term memory impairment, both lure types induce the same amount of intrusions. These findings indicate that usually phonological information is retained in sentence recall in addition to semantic information.

Information integration from heterogeneous data sources: a Semantic Web approach.

PubMed

Kunapareddy, Narendra; Mirhaji, Parsa; Richards, David; Casscells, S Ward

2006-01-01

Although the decentralized and autonomous implementation of health information systems has made it possible to extend the reach of surveillance systems to a variety of contextually disparate domains, public health use of data from these systems is not primarily anticipated. The Semantic Web has been proposed to address both representational and semantic heterogeneity in distributed and collaborative environments. We introduce a semantic approach for the integration of health data using the Resource Definition Framework (RDF) and the Simple Knowledge Organization System (SKOS) developed by the Semantic Web community.

Hybrid ontology for semantic information retrieval model using keyword matching indexing system.

PubMed

Uthayan, K R; Mala, G S Anandha

2015-01-01

Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.

Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System

PubMed Central

Uthayan, K. R.; Anandha Mala, G. S.

2015-01-01

Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology. PMID:25922851

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)…

Speaker information affects false recognition of unstudied lexical-semantic associates.

PubMed

Luthra, Sahil; Fox, Neal P; Blumstein, Sheila E

2018-05-01

Recognition of and memory for a spoken word can be facilitated by a prior presentation of that word spoken by the same talker. However, it is less clear whether this speaker congruency advantage generalizes to facilitate recognition of unheard related words. The present investigation employed a false memory paradigm to examine whether information about a speaker's identity in items heard by listeners could influence the recognition of novel items (critical intruders) phonologically or semantically related to the studied items. In Experiment 1, false recognition of semantically associated critical intruders was sensitive to speaker information, though only when subjects attended to talker identity during encoding. Results from Experiment 2 also provide some evidence that talker information affects the false recognition of critical intruders. Taken together, the present findings indicate that indexical information is able to contact the lexical-semantic network to affect the processing of unheard words.

Exploiting salient semantic analysis for information retrieval

NASA Astrophysics Data System (ADS)

Luo, Jing; Meng, Bo; Quan, Changqin; Tu, Xinhui

2016-11-01

Recently, many Wikipedia-based methods have been proposed to improve the performance of different natural language processing (NLP) tasks, such as semantic relatedness computation, text classification and information retrieval. Among these methods, salient semantic analysis (SSA) has been proven to be an effective way to generate conceptual representation for words or documents. However, its feasibility and effectiveness in information retrieval is mostly unknown. In this paper, we study how to efficiently use SSA to improve the information retrieval performance, and propose a SSA-based retrieval method under the language model framework. First, SSA model is adopted to build conceptual representations for documents and queries. Then, these conceptual representations and the bag-of-words (BOW) representations can be used in combination to estimate the language models of queries and documents. The proposed method is evaluated on several standard text retrieval conference (TREC) collections. Experiment results on standard TREC collections show the proposed models consistently outperform the existing Wikipedia-based retrieval methods.

Adapting Semantic Natural Language Processing Technology to Address Information Overload in Influenza Epidemic Management

PubMed Central

Keselman, Alla; Rosemblat, Graciela; Kilicoglu, Halil; Fiszman, Marcelo; Jin, Honglan; Shin, Dongwook; Rindflesch, Thomas C.

2013-01-01

Explosion of disaster health information results in information overload among response professionals. The objective of this project was to determine the feasibility of applying semantic natural language processing (NLP) technology to addressing this overload. The project characterizes concepts and relationships commonly used in disaster health-related documents on influenza pandemics, as the basis for adapting an existing semantic summarizer to the domain. Methods include human review and semantic NLP analysis of a set of relevant documents. This is followed by a pilot-test in which two information specialists use the adapted application for a realistic information seeking task. According to the results, the ontology of influenza epidemics management can be described via a manageable number of semantic relationships that involve concepts from a limited number of semantic types. Test users demonstrate several ways to engage with the application to obtain useful information. This suggests that existing semantic NLP algorithms can be adapted to support information summarization and visualization in influenza epidemics and other disaster health areas. However, additional research is needed in the areas of terminology development (as many relevant relationships and terms are not part of existing standardized vocabularies), NLP, and user interface design. PMID:24311971

Developmental changes in the neural influence of sublexical information on semantic processing.

PubMed

Lee, Shu-Hui; Booth, James R; Chou, Tai-Li

2015-07-01

Functional magnetic resonance imaging (fMRI) was used to examine the developmental changes in a group of normally developing children (aged 8-12) and adolescents (aged 13-16) during semantic processing. We manipulated association strength (i.e. a global reading unit) and semantic radical (i.e. a local reading unit) to explore the interaction of lexical and sublexical semantic information in making semantic judgments. In the semantic judgment task, two types of stimuli were used: visually-similar (i.e. shared a semantic radical) versus visually-dissimilar (i.e. did not share a semantic radical) character pairs. Participants were asked to indicate if two Chinese characters, arranged according to association strength, were related in meaning. The results showed greater developmental increases in activation in left angular gyrus (BA 39) in the visually-similar compared to the visually-dissimilar pairs for the strong association. There were also greater age-related increases in angular gyrus for the strong compared to weak association in the visually-similar pairs. Both of these results suggest that shared semantics at the sublexical level facilitates the integration of overlapping features at the lexical level in older children. In addition, there was a larger developmental increase in left posterior middle temporal gyrus (BA 21) for the weak compared to strong association in the visually-dissimilar pairs, suggesting conflicting sublexical information placed greater demands on access to lexical representations in the older children. All together, these results suggest that older children are more sensitive to sublexical information when processing lexical representations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Operationalizing Semantic Medline for meeting the information needs at point of care.

PubMed

Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

2015-01-01

Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible.

Operationalizing Semantic Medline for meeting the information needs at point of care

PubMed Central

Rastegar-Mojarad, Majid; Li, Dingcheng; Liu, Hongfang

2015-01-01

Scientific literature is one of the popular resources for providing decision support at point of care. It is highly desirable to bring the most relevant literature to support the evidence-based clinical decision making process. Motivated by the recent advance in semantically enhanced information retrieval, we have developed a system, which aims to bring semantically enriched literature, Semantic Medline, to meet the information needs at point of care. This study reports our work towards operationalizing the system for real time use. We demonstrate that the migration of a relational database implementation to a NoSQL (Not only SQL) implementation significantly improves the performance and makes the use of Semantic Medline at point of care decision support possible. PMID:26306259

Less Is More: Semantic Information Survives Interocular Suppression When Attention Is Diverted.

PubMed

Eo, Kangyong; Cha, Oakyoon; Chong, Sang Chul; Kang, Min-Suk

2016-05-18

The extent of unconscious semantic processing has been debated. It is well established that semantic information is registered in the absence of awareness induced by inattention. However, it has been debated whether semantic information of invisible stimuli is processed during interocular suppression, a procedure that renders one eye's view invisible by presenting a dissimilar stimulus to the other eye. Inspired by recent evidence demonstrating that reduced attention attenuates interocular suppression, we tested a counterintuitive hypothesis that attention withdrawn from the suppressed target location facilitates semantic processing in the absence of awareness induced by interocular suppression. We obtained an electrophysiological marker of semantic processing (N400 component) while human participants' spatial attention was being manipulated with a cueing paradigm during interocular suppression. We found that N400 modulation was absent when participants' attention was directed to the target location, but present when diverted elsewhere. In addition, the correlation analysis across participants indicated that the N400 amplitude was reduced with more attention being directed to the target location. Together, these results indicate that inattention attenuates interocular suppression and thereby makes semantic processing available unconsciously, reconciling conflicting evidence in the literature. We discuss a tight link among interocular suppression, attention, and conscious awareness. Interocular suppression offers a powerful means of studying the extent of unconscious processing by rendering a salient stimulus presented to one eye invisible. Here, we provide evidence that attention is a determining factor for unconscious semantic processing. An electrophysiological marker for semantic processing (N400 component) was present when attention was diverted away from the suppressed stimulus but absent when attention was directed to that stimulus, indicating that

Dynamic information processing states revealed through neurocognitive models of object semantics

PubMed Central

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

Life, Information, Entropy, and Time: Vehicles for Semantic Inheritance.

PubMed

Crofts, Antony R

2007-01-01

Attempts to understand how information content can be included in an accounting of the energy flux of the biosphere have led to the conclusion that, in information transmission, one component, the semantic content, or "the meaning of the message," adds no thermodynamic burden over and above costs arising from coding, transmission and translation. In biology, semantic content has two major roles. For all life forms, the message of the genotype encoded in DNA specifies the phenotype, and hence the organism that is tested against the real world through the mechanisms of Darwinian evolution. For human beings, communication through language and similar abstractions provides an additional supra-phenotypic vehicle for semantic inheritance, which supports the cultural heritages around which civilizations revolve. The following three postulates provide the basis for discussion of a number of themes that demonstrate some important consequences. (i) Information transmission through either pathway has thermodynamic components associated with data storage and transmission. (ii) The semantic content adds no additional thermodynamic cost. (iii) For all semantic exchange, meaning is accessible only through translation and interpretation, and has a value only in context. (1) For both pathways of semantic inheritance, translational and copying machineries are imperfect. As a consequence both pathways are subject to mutation and to evolutionary pressure by selection. Recognition of semantic content as a common component allows an understanding of the relationship between genes and memes, and a reformulation of Universal Darwinism. (2) The emergent properties of life are dependent on a processing of semantic content. The translational steps allow amplification in complexity through combinatorial possibilities in space and time. Amplification depends on the increased potential for complexity opened by 3D interaction specificity of proteins, and on the selection of useful variants by

Examining the Hemispheric Distribution of Semantic Information Using Lateralised Priming of Familiar Faces

ERIC Educational Resources Information Center

Vladeanu, Matei; Bourne, Victoria J.

2009-01-01

The way in which the semantic information associated with people is organised in the brain is still unclear. Most evidence suggests either bilateral or left hemisphere lateralisation. In this paper we use a lateralised semantic priming paradigm to further examine this neuropsychological organisation. A clear semantic priming effect was found with…

Biomedical semantics in the Semantic Web

PubMed Central

2011-01-01

The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences? We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th. PMID:21388570

Biomedical semantics in the Semantic Web.

PubMed

Splendiani, Andrea; Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott

2011-03-07

The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th.

Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures.

PubMed

Li, Lishuang; Zhang, Panpan; Zheng, Tianfu; Zhang, Hongying; Jiang, Zhenchao; Huang, Degen

2014-01-01

Protein-Protein Interaction (PPI) extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were basically ignored. In this paper, we propose a multiple-kernel learning-based approach to extract PPIs, combining the feature-based kernel, tree kernel and semantic kernel. Particularly, we extend the shortest path-enclosed tree kernel (SPT) by a dynamic extended strategy to retrieve the richer syntactic information. Our semantic kernel calculates the protein-protein pair similarity and the context similarity based on two semantic resources: WordNet and Medical Subject Heading (MeSH). We evaluate our method with Support Vector Machine (SVM) and achieve an F-score of 69.40% and an AUC of 92.00%, which show that our method outperforms most of the state-of-the-art systems by integrating semantic information.

Semantic-Based Information Retrieval of Biomedical Data

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

Jiao, Yu; Potok, Thomas E; Hurson, Ali R.

In this paper, we propose to improve the effectiveness of biomedical information retrieval via a medical thesaurus. We analyzed the deficiencies of the existing medical thesauri and reconstructed a new thesaurus, called MEDTHES, which follows the ANSI/NISO Z39.19-2003 standard. MEDTHES also endows the users with fine-grained control of information retrieval by providing functions to calculate the semantic similarity between words. We demonstrate the usage of MEDTHES through an existing data search engine.

Building a biomedical semantic network in Wikipedia with Semantic Wiki Links

PubMed Central

Good, Benjamin M.; Clarke, Erik L.; Loguercio, Salvatore; Su, Andrew I.

2012-01-01

Wikipedia is increasingly used as a platform for collaborative data curation, but its current technical implementation has significant limitations that hinder its use in biocuration applications. Specifically, while editors can easily link between two articles in Wikipedia to indicate a relationship, there is no way to indicate the nature of that relationship in a way that is computationally accessible to the system or to external developers. For example, in addition to noting a relationship between a gene and a disease, it would be useful to differentiate the cases where genetic mutation or altered expression causes the disease. Here, we introduce a straightforward method that allows Wikipedia editors to embed computable semantic relations directly in the context of current Wikipedia articles. In addition, we demonstrate two novel applications enabled by the presence of these new relationships. The first is a dynamically generated information box that can be rendered on all semantically enhanced Wikipedia articles. The second is a prototype gene annotation system that draws its content from the gene-centric articles on Wikipedia and exposes the new semantic relationships to enable previously impossible, user-defined queries. Database URL: http://en.wikipedia.org/wiki/Portal:Gene_Wiki PMID:22434829

Building a biomedical semantic network in Wikipedia with Semantic Wiki Links.

PubMed

Good, Benjamin M; Clarke, Erik L; Loguercio, Salvatore; Su, Andrew I

2012-01-01

Wikipedia is increasingly used as a platform for collaborative data curation, but its current technical implementation has significant limitations that hinder its use in biocuration applications. Specifically, while editors can easily link between two articles in Wikipedia to indicate a relationship, there is no way to indicate the nature of that relationship in a way that is computationally accessible to the system or to external developers. For example, in addition to noting a relationship between a gene and a disease, it would be useful to differentiate the cases where genetic mutation or altered expression causes the disease. Here, we introduce a straightforward method that allows Wikipedia editors to embed computable semantic relations directly in the context of current Wikipedia articles. In addition, we demonstrate two novel applications enabled by the presence of these new relationships. The first is a dynamically generated information box that can be rendered on all semantically enhanced Wikipedia articles. The second is a prototype gene annotation system that draws its content from the gene-centric articles on Wikipedia and exposes the new semantic relationships to enable previously impossible, user-defined queries. DATABASE URL: http://en.wikipedia.org/wiki/Portal:Gene_Wiki.

Bim-Gis Integrated Geospatial Information Model Using Semantic Web and Rdf Graphs

NASA Astrophysics Data System (ADS)

Hor, A.-H.; Jadidi, A.; Sohn, G.

2016-06-01

In recent years, 3D virtual indoor/outdoor urban modelling becomes a key spatial information framework for many civil and engineering applications such as evacuation planning, emergency and facility management. For accomplishing such sophisticate decision tasks, there is a large demands for building multi-scale and multi-sourced 3D urban models. Currently, Building Information Model (BIM) and Geographical Information Systems (GIS) are broadly used as the modelling sources. However, data sharing and exchanging information between two modelling domains is still a huge challenge; while the syntactic or semantic approaches do not fully provide exchanging of rich semantic and geometric information of BIM into GIS or vice-versa. This paper proposes a novel approach for integrating BIM and GIS using semantic web technologies and Resources Description Framework (RDF) graphs. The novelty of the proposed solution comes from the benefits of integrating BIM and GIS technologies into one unified model, so-called Integrated Geospatial Information Model (IGIM). The proposed approach consists of three main modules: BIM-RDF and GIS-RDF graphs construction, integrating of two RDF graphs, and query of information through IGIM-RDF graph using SPARQL. The IGIM generates queries from both the BIM and GIS RDF graphs resulting a semantically integrated model with entities representing both BIM classes and GIS feature objects with respect to the target-client application. The linkage between BIM-RDF and GIS-RDF is achieved through SPARQL endpoints and defined by a query using set of datasets and entity classes with complementary properties, relationships and geometries. To validate the proposed approach and its performance, a case study was also tested using IGIM system design.

Methods and apparatus for capture and storage of semantic information with sub-files in a parallel computing system

DOEpatents

Faibish, Sorin; Bent, John M; Tzelnic, Percy; Grider, Gary; Torres, Aaron

2015-02-03

Techniques are provided for storing files in a parallel computing system using sub-files with semantically meaningful boundaries. A method is provided for storing at least one file generated by a distributed application in a parallel computing system. The file comprises one or more of a complete file and a plurality of sub-files. The method comprises the steps of obtaining a user specification of semantic information related to the file; providing the semantic information as a data structure description to a data formatting library write function; and storing the semantic information related to the file with one or more of the sub-files in one or more storage nodes of the parallel computing system. The semantic information provides a description of data in the file. The sub-files can be replicated based on semantically meaningful boundaries.

The role of sleep spindles and slow-wave activity in integrating new information in semantic memory.

PubMed

Tamminen, Jakke; Lambon Ralph, Matthew A; Lewis, Penelope A

2013-09-25

Assimilating new information into existing knowledge is a fundamental part of consolidating new memories and allowing them to guide behavior optimally and is vital for conceptual knowledge (semantic memory), which is accrued over many years. Sleep is important for memory consolidation, but its impact upon assimilation of new information into existing semantic knowledge has received minimal examination. Here, we examined the integration process by training human participants on novel words with meanings that fell into densely or sparsely populated areas of semantic memory in two separate sessions. Overnight sleep was polysomnographically monitored after each training session and recall was tested immediately after training, after a night of sleep, and 1 week later. Results showed that participants learned equal numbers of both word types, thus equating amount and difficulty of learning across the conditions. Measures of word recognition speed showed a disadvantage for novel words in dense semantic neighborhoods, presumably due to interference from many semantically related concepts, suggesting that the novel words had been successfully integrated into semantic memory. Most critically, semantic neighborhood density influenced sleep architecture, with participants exhibiting more sleep spindles and slow-wave activity after learning the sparse compared with the dense neighborhood words. These findings provide the first evidence that spindles and slow-wave activity mediate integration of new information into existing semantic networks.

Behavior Modification Through Covert Semantic Desensitization

ERIC Educational Resources Information Center

Hekmat, Hamid; Vanian, Daniel

1971-01-01

Results support the hypothesized relationship between meaning and phobia. Semantic desensitization techniques based on counter conditioning of meaning were significantly effective in altering the semantic value of the word from unpleasantness to neutrality. (Author)

Integrating semantic web technologies and geospatial catalog services for geospatial information discovery and processing in cyberinfrastructure

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

Yue, Peng; Gong, Jianya; Di, Liping

Abstract A geospatial catalogue service provides a network-based meta-information repository and interface for advertising and discovering shared geospatial data and services. Descriptive information (i.e., metadata) for geospatial data and services is structured and organized in catalogue services. The approaches currently available for searching and using that information are often inadequate. Semantic Web technologies show promise for better discovery methods by exploiting the underlying semantics. Such development needs special attention from the Cyberinfrastructure perspective, so that the traditional focus on discovery of and access to geospatial data can be expanded to support the increased demand for processing of geospatial information andmore » discovery of knowledge. Semantic descriptions for geospatial data, services, and geoprocessing service chains are structured, organized, and registered through extending elements in the ebXML Registry Information Model (ebRIM) of a geospatial catalogue service, which follows the interface specifications of the Open Geospatial Consortium (OGC) Catalogue Services for the Web (CSW). The process models for geoprocessing service chains, as a type of geospatial knowledge, are captured, registered, and discoverable. Semantics-enhanced discovery for geospatial data, services/service chains, and process models is described. Semantic search middleware that can support virtual data product materialization is developed for the geospatial catalogue service. The creation of such a semantics-enhanced geospatial catalogue service is important in meeting the demands for geospatial information discovery and analysis in Cyberinfrastructure.« less

A Novel Software Architecture for the Provision of Context-Aware Semantic Transport Information

PubMed Central

Moreno, Asier; Perallos, Asier; López-de-Ipiña, Diego; Onieva, Enrique; Salaberria, Itziar; Masegosa, Antonio D.

2015-01-01

The effectiveness of Intelligent Transportation Systems depends largely on the ability to integrate information from diverse sources and the suitability of this information for the specific user. This paper describes a new approach for the management and exchange of this information, related to multimodal transportation. A novel software architecture is presented, with particular emphasis on the design of the data model and the enablement of services for information retrieval, thereby obtaining a semantic model for the representation of transport information. The publication of transport data as semantic information is established through the development of a Multimodal Transport Ontology (MTO) and the design of a distributed architecture allowing dynamic integration of transport data. The advantages afforded by the proposed system due to the use of Linked Open Data and a distributed architecture are stated, comparing it with other existing solutions. The adequacy of the information generated in regard to the specific user’s context is also addressed. Finally, a working solution of a semantic trip planner using actual transport data and running on the proposed architecture is presented, as a demonstration and validation of the system. PMID:26016915

A novel software architecture for the provision of context-aware semantic transport information.

PubMed

Moreno, Asier; Perallos, Asier; López-de-Ipiña, Diego; Onieva, Enrique; Salaberria, Itziar; Masegosa, Antonio D

2015-05-26

The effectiveness of Intelligent Transportation Systems depends largely on the ability to integrate information from diverse sources and the suitability of this information for the specific user. This paper describes a new approach for the management and exchange of this information, related to multimodal transportation. A novel software architecture is presented, with particular emphasis on the design of the data model and the enablement of services for information retrieval, thereby obtaining a semantic model for the representation of transport information. The publication of transport data as semantic information is established through the development of a Multimodal Transport Ontology (MTO) and the design of a distributed architecture allowing dynamic integration of transport data. The advantages afforded by the proposed system due to the use of Linked Open Data and a distributed architecture are stated, comparing it with other existing solutions. The adequacy of the information generated in regard to the specific user's context is also addressed. Finally, a working solution of a semantic trip planner using actual transport data and running on the proposed architecture is presented, as a demonstration and validation of the system.

Latent morpho-semantic analysis : multilingual information retrieval with character n-grams and mutual information.

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

Bader, Brett William; Chew, Peter A.; Abdelali, Ahmed

We describe an entirely statistics-based, unsupervised, and language-independent approach to multilingual information retrieval, which we call Latent Morpho-Semantic Analysis (LMSA). LMSA overcomes some of the shortcomings of related previous approaches such as Latent Semantic Analysis (LSA). LMSA has an important theoretical advantage over LSA: it combines well-known techniques in a novel way to break the terms of LSA down into units which correspond more closely to morphemes. Thus, it has a particular appeal for use with morphologically complex languages such as Arabic. We show through empirical results that the theoretical advantages of LMSA can translate into significant gains in precisionmore » in multilingual information retrieval tests. These gains are not matched either when a standard stemmer is used with LSA, or when terms are indiscriminately broken down into n-grams.« less

The semantic distance task: Quantifying semantic distance with semantic network path length.

PubMed

Kenett, Yoed N; Levi, Effi; Anaki, David; Faust, Miriam

2017-09-01

Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We propose a novel approach to computing semantic distance, based on network science methodology. Path length in a semantic network represents the amount of steps needed to traverse from 1 word in the network to the other. We examine whether path length can be used as a measure of semantic distance, by investigating how path length affect performance in a semantic relatedness judgment task and recall from memory. Our results show a differential effect on performance: Up to 4 steps separating between word-pairs, participants exhibit an increase in reaction time (RT) and decrease in the percentage of word-pairs judged as related. From 4 steps onward, participants exhibit a significant decrease in RT and the word-pairs are dominantly judged as unrelated. Furthermore, we show that as path length between word-pairs increases, success in free- and cued-recall decreases. Finally, we demonstrate how our measure outperforms computational methods measuring semantic distance (LSA and positive pointwise mutual information) in predicting participants RT and subjective judgments of semantic strength. Thus, we provide a computational alternative to computing semantic distance. Furthermore, this approach addresses key issues in cognitive theory, namely the breadth of the spreading activation process and the effect of semantic distance on memory retrieval. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Semantator: semantic annotator for converting biomedical text to linked data.

PubMed

Tao, Cui; Song, Dezhao; Sharma, Deepak; Chute, Christopher G

2013-10-01

More than 80% of biomedical data is embedded in plain text. The unstructured nature of these text-based documents makes it challenging to easily browse and query the data of interest in them. One approach to facilitate browsing and querying biomedical text is to convert the plain text to a linked web of data, i.e., converting data originally in free text to structured formats with defined meta-level semantics. In this paper, we introduce Semantator (Semantic Annotator), a semantic-web-based environment for annotating data of interest in biomedical documents, browsing and querying the annotated data, and interactively refining annotation results if needed. Through Semantator, information of interest can be either annotated manually or semi-automatically using plug-in information extraction tools. The annotated results will be stored in RDF and can be queried using the SPARQL query language. In addition, semantic reasoners can be directly applied to the annotated data for consistency checking and knowledge inference. Semantator has been released online and was used by the biomedical ontology community who provided positive feedbacks. Our evaluation results indicated that (1) Semantator can perform the annotation functionalities as designed; (2) Semantator can be adopted in real applications in clinical and transactional research; and (3) the annotated results using Semantator can be easily used in Semantic-web-based reasoning tools for further inference. Copyright © 2013 Elsevier Inc. All rights reserved.

The semantic representation of event information depends on the cue modality: an instance of meaning-based retrieval.

PubMed

Karlsson, Kristina; Sikström, Sverker; Willander, Johan

2013-01-01

The semantic content, or the meaning, is the essence of autobiographical memories. In comparison to previous research, which has mainly focused on the phenomenological experience and the age distribution of retrieved events, the present study provides a novel view on the retrieval of event information by quantifying the information as semantic representations. We investigated the semantic representation of sensory cued autobiographical events and studied the modality hierarchy within the multimodal retrieval cues. The experiment comprised a cued recall task, where the participants were presented with visual, auditory, olfactory or multimodal retrieval cues and asked to recall autobiographical events. The results indicated that the three different unimodal retrieval cues generate significantly different semantic representations. Further, the auditory and the visual modalities contributed the most to the semantic representation of the multimodally retrieved events. Finally, the semantic representation of the multimodal condition could be described as a combination of the three unimodal conditions. In conclusion, these results suggest that the meaning of the retrieved event information depends on the modality of the retrieval cues.

The Semantic Representation of Event Information Depends on the Cue Modality: An Instance of Meaning-Based Retrieval

PubMed Central

Karlsson, Kristina; Sikström, Sverker; Willander, Johan

2013-01-01

The semantic content, or the meaning, is the essence of autobiographical memories. In comparison to previous research, which has mainly focused on the phenomenological experience and the age distribution of retrieved events, the present study provides a novel view on the retrieval of event information by quantifying the information as semantic representations. We investigated the semantic representation of sensory cued autobiographical events and studied the modality hierarchy within the multimodal retrieval cues. The experiment comprised a cued recall task, where the participants were presented with visual, auditory, olfactory or multimodal retrieval cues and asked to recall autobiographical events. The results indicated that the three different unimodal retrieval cues generate significantly different semantic representations. Further, the auditory and the visual modalities contributed the most to the semantic representation of the multimodally retrieved events. Finally, the semantic representation of the multimodal condition could be described as a combination of the three unimodal conditions. In conclusion, these results suggest that the meaning of the retrieved event information depends on the modality of the retrieval cues. PMID:24204561

Getting connected: Both associative and semantic links structure semantic memory for newly learned persons.

PubMed

Wiese, Holger; Schweinberger, Stefan R

2015-01-01

The present study examined whether semantic memory for newly learned people is structured by visual co-occurrence, shared semantics, or both. Participants were trained with pairs of simultaneously presented (i.e., co-occurring) preexperimentally unfamiliar faces, which either did or did not share additionally provided semantic information (occupation, place of living, etc.). Semantic information could also be shared between faces that did not co-occur. A subsequent priming experiment revealed faster responses for both co-occurrence/no shared semantics and no co-occurrence/shared semantics conditions, than for an unrelated condition. Strikingly, priming was strongest in the co-occurrence/shared semantics condition, suggesting additive effects of these factors. Additional analysis of event-related brain potentials yielded priming in the N400 component only for combined effects of visual co-occurrence and shared semantics, with more positive amplitudes in this than in the unrelated condition. Overall, these findings suggest that both semantic relatedness and visual co-occurrence are important when novel information is integrated into person-related semantic memory.

A trade-off between local and distributed information processing associated with remote episodic versus semantic memory.

PubMed

Heisz, Jennifer J; Vakorin, Vasily; Ross, Bernhard; Levine, Brian; McIntosh, Anthony R

2014-01-01

Episodic memory and semantic memory produce very different subjective experiences yet rely on overlapping networks of brain regions for processing. Traditional approaches for characterizing functional brain networks emphasize static states of function and thus are blind to the dynamic information processing within and across brain regions. This study used information theoretic measures of entropy to quantify changes in the complexity of the brain's response as measured by magnetoencephalography while participants listened to audio recordings describing past personal episodic and general semantic events. Personal episodic recordings evoked richer subjective mnemonic experiences and more complex brain responses than general semantic recordings. Critically, we observed a trade-off between the relative contribution of local versus distributed entropy, such that personal episodic recordings produced relatively more local entropy whereas general semantic recordings produced relatively more distributed entropy. Changes in the relative contributions of local and distributed entropy to the total complexity of the system provides a potential mechanism that allows the same network of brain regions to represent cognitive information as either specific episodes or more general semantic knowledge.

A Semantic Graph Query Language

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

Kaplan, I L

2006-10-16

Semantic graphs can be used to organize large amounts of information from a number of sources into one unified structure. A semantic query language provides a foundation for extracting information from the semantic graph. The graph query language described here provides a simple, powerful method for querying semantic graphs.

Explaining semantic short-term memory deficits: Evidence for the critical role of semantic control

PubMed Central

Hoffman, Paul; Jefferies, Elizabeth; Lambon Ralph, Matthew A.

2011-01-01

Patients with apparently selective short-term memory (STM) deficits for semantic information have played an important role in developing multi-store theories of STM and challenge the idea that verbal STM is supported by maintaining activation in the language system. We propose that semantic STM deficits are not as selective as previously thought and can occur as a result of mild disruption to semantic control processes, i.e., mechanisms that bias semantic processing towards task-relevant aspects of knowledge and away from irrelevant information. We tested three semantic STM patients with tasks that tapped four aspects of semantic control: (i) resolving ambiguity between word meanings, (ii) sensitivity to cues, (iii) ignoring irrelevant information and (iv) detecting weak semantic associations. All were impaired in conditions requiring more semantic control, irrespective of the STM demands of the task, suggesting a mild, but task-general, deficit in regulating semantic knowledge. This mild deficit has a disproportionate effect on STM tasks because they have high intrinsic control demands: in STM tasks, control is required to keep information active when it is no longer available in the environment and to manage competition between items held in memory simultaneously. By re-interpreting the core deficit in semantic STM patients in this way, we are able to explain their apparently selective impairment without the need for a specialised STM store. Instead, we argue that semantic STM patients occupy the mildest end of spectrum of semantic control disorders. PMID:21195105

A semantic model for multimodal data mining in healthcare information systems.

PubMed

Iakovidis, Dimitris; Smailis, Christos

2012-01-01

Electronic health records (EHRs) are representative examples of multimodal/multisource data collections; including measurements, images and free texts. The diversity of such information sources and the increasing amounts of medical data produced by healthcare institutes annually, pose significant challenges in data mining. In this paper we present a novel semantic model that describes knowledge extracted from the lowest-level of a data mining process, where information is represented by multiple features i.e. measurements or numerical descriptors extracted from measurements, images, texts or other medical data, forming multidimensional feature spaces. Knowledge collected by manual annotation or extracted by unsupervised data mining from one or more feature spaces is modeled through generalized qualitative spatial semantics. This model enables a unified representation of knowledge across multimodal data repositories. It contributes to bridging the semantic gap, by enabling direct links between low-level features and higher-level concepts e.g. describing body parts, anatomies and pathological findings. The proposed model has been developed in web ontology language based on description logics (OWL-DL) and can be applied to a variety of data mining tasks in medical informatics. It utility is demonstrated for automatic annotation of medical data.

The Construction of Semantic Memory: Grammar-Based Representations Learned from Relational Episodic Information

PubMed Central

Battaglia, Francesco P.; Pennartz, Cyriel M. A.

2011-01-01

After acquisition, memories underlie a process of consolidation, making them more resistant to interference and brain injury. Memory consolidation involves systems-level interactions, most importantly between the hippocampus and associated structures, which takes part in the initial encoding of memory, and the neocortex, which supports long-term storage. This dichotomy parallels the contrast between episodic memory (tied to the hippocampal formation), collecting an autobiographical stream of experiences, and semantic memory, a repertoire of facts and statistical regularities about the world, involving the neocortex at large. Experimental evidence points to a gradual transformation of memories, following encoding, from an episodic to a semantic character. This may require an exchange of information between different memory modules during inactive periods. We propose a theory for such interactions and for the formation of semantic memory, in which episodic memory is encoded as relational data. Semantic memory is modeled as a modified stochastic grammar, which learns to parse episodic configurations expressed as an association matrix. The grammar produces tree-like representations of episodes, describing the relationships between its main constituents at multiple levels of categorization, based on its current knowledge of world regularities. These regularities are learned by the grammar from episodic memory information, through an expectation-maximization procedure, analogous to the inside–outside algorithm for stochastic context-free grammars. We propose that a Monte-Carlo sampling version of this algorithm can be mapped on the dynamics of “sleep replay” of previously acquired information in the hippocampus and neocortex. We propose that the model can reproduce several properties of semantic memory such as decontextualization, top-down processing, and creation of schemata. PMID:21887143

Representing nested semantic information in a linear string of text using XML.

PubMed

Krauthammer, Michael; Johnson, Stephen B; Hripcsak, George; Campbell, David A; Friedman, Carol

2002-01-01

XML has been widely adopted as an important data interchange language. The structure of XML enables sharing of data elements with variable degrees of nesting as long as the elements are grouped in a strict tree-like fashion. This requirement potentially restricts the usefulness of XML for marking up written text, which often includes features that do not properly nest within other features. We encountered this problem while marking up medical text with structured semantic information from a Natural Language Processor. Traditional approaches to this problem separate the structured information from the actual text mark up. This paper introduces an alternative solution, which tightly integrates the semantic structure with the text. The resulting XML markup preserves the linearity of the medical texts and can therefore be easily expanded with additional types of information.

Representing nested semantic information in a linear string of text using XML.

PubMed Central

Krauthammer, Michael; Johnson, Stephen B.; Hripcsak, George; Campbell, David A.; Friedman, Carol

2002-01-01

XML has been widely adopted as an important data interchange language. The structure of XML enables sharing of data elements with variable degrees of nesting as long as the elements are grouped in a strict tree-like fashion. This requirement potentially restricts the usefulness of XML for marking up written text, which often includes features that do not properly nest within other features. We encountered this problem while marking up medical text with structured semantic information from a Natural Language Processor. Traditional approaches to this problem separate the structured information from the actual text mark up. This paper introduces an alternative solution, which tightly integrates the semantic structure with the text. The resulting XML markup preserves the linearity of the medical texts and can therefore be easily expanded with additional types of information. PMID:12463856

Care episode retrieval: distributional semantic models for information retrieval in the clinical domain.

PubMed

Moen, Hans; Ginter, Filip; Marsi, Erwin; Peltonen, Laura-Maria; Salakoski, Tapio; Salanterä, Sanna

2015-01-01

Patients' health related information is stored in electronic health records (EHRs) by health service providers. These records include sequential documentation of care episodes in the form of clinical notes. EHRs are used throughout the health care sector by professionals, administrators and patients, primarily for clinical purposes, but also for secondary purposes such as decision support and research. The vast amounts of information in EHR systems complicate information management and increase the risk of information overload. Therefore, clinicians and researchers need new tools to manage the information stored in the EHRs. A common use case is, given a--possibly unfinished--care episode, to retrieve the most similar care episodes among the records. This paper presents several methods for information retrieval, focusing on care episode retrieval, based on textual similarity, where similarity is measured through domain-specific modelling of the distributional semantics of words. Models include variants of random indexing and the semantic neural network model word2vec. Two novel methods are introduced that utilize the ICD-10 codes attached to care episodes to better induce domain-specificity in the semantic model. We report on experimental evaluation of care episode retrieval that circumvents the lack of human judgements regarding episode relevance. Results suggest that several of the methods proposed outperform a state-of-the art search engine (Lucene) on the retrieval task.

Care episode retrieval: distributional semantic models for information retrieval in the clinical domain

PubMed Central

2015-01-01

Patients' health related information is stored in electronic health records (EHRs) by health service providers. These records include sequential documentation of care episodes in the form of clinical notes. EHRs are used throughout the health care sector by professionals, administrators and patients, primarily for clinical purposes, but also for secondary purposes such as decision support and research. The vast amounts of information in EHR systems complicate information management and increase the risk of information overload. Therefore, clinicians and researchers need new tools to manage the information stored in the EHRs. A common use case is, given a - possibly unfinished - care episode, to retrieve the most similar care episodes among the records. This paper presents several methods for information retrieval, focusing on care episode retrieval, based on textual similarity, where similarity is measured through domain-specific modelling of the distributional semantics of words. Models include variants of random indexing and the semantic neural network model word2vec. Two novel methods are introduced that utilize the ICD-10 codes attached to care episodes to better induce domain-specificity in the semantic model. We report on experimental evaluation of care episode retrieval that circumvents the lack of human judgements regarding episode relevance. Results suggest that several of the methods proposed outperform a state-of-the art search engine (Lucene) on the retrieval task. PMID:26099735

Semantics of data and service registration to advance interdisciplinary information and data access.

NASA Astrophysics Data System (ADS)

Fox, P. P.; McGuinness, D. L.; Raskin, R.; Sinha, A. K.

2008-12-01

In developing an application of semantic web methods and technologies to address the integration of heterogeneous and interdisciplinary earth-science datasets, we have developed methodologies for creating rich semantic descriptions (ontologies) of the application domains. We have leveraged and extended where possible existing ontology frameworks such as SWEET. As a result of this semantic approach, we have also utilized ontologic descriptions of key enabling elements of the application, such as the registration of datasets with ontologies at several levels of granularity. This has enabled the location and usage of the data across disciplines. We are also realizing the need to develop similar semantic registration of web service data holdings as well as those provided with community and/or standard markup languages (e.g. GeoSciML). This level of semantic enablement extending beyond domain terms and relations significantly enhances our ability to provide a coherent semantic data framework for data and information systems. Much of this work is on the frontier of technology development and we will present the current and near-future capabilities we are developing. This work arises from the Semantically-Enabled Science Data Integration (SESDI) project, which is an NASA/ESTO/ACCESS-funded project involving the High Altitude Observatory at the National Center for Atmospheric Research (NCAR), McGuinness Associates Consulting, NASA/JPL and Virginia Polytechnic University.

Altered Neural Activity during Semantic Object Memory Retrieval in Amnestic Mild Cognitive Impairment as Measured by Event-Related Potentials.

PubMed

Chiang, Hsueh-Sheng; Mudar, Raksha A; Pudhiyidath, Athula; Spence, Jeffrey S; Womack, Kyle B; Cullum, C Munro; Tanner, Jeremy A; Eroh, Justin; Kraut, Michael A; Hart, John

2015-01-01

Deficits in semantic memory in individuals with amnestic mild cognitive impairment (aMCI) have been previously reported, but the underlying neurobiological mechanisms remain to be clarified. We examined event-related potentials (ERPs) associated with semantic memory retrieval in 16 individuals with aMCI as compared to 17 normal controls using the Semantic Object Retrieval Task (EEG SORT). In this task, subjects judged whether pairs of words (object features) elicited retrieval of an object (retrieval trials) or not (non-retrieval trials). Behavioral findings revealed that aMCI subjects had lower accuracy scores and marginally longer reaction time compared to controls. We used a multivariate analytical technique (STAT-PCA) to investigate similarities and differences in ERPs between aMCI and control groups. STAT-PCA revealed a left fronto-temporal component starting at around 750 ms post-stimulus in both groups. However, unlike controls, aMCI subjects showed an increase in the frontal-parietal scalp potential that distinguished retrieval from non-retrieval trials between 950 and 1050 ms post-stimulus negatively correlated with the performance on the logical memory subtest of the Wechsler Memory Scale-III. Thus, individuals with aMCI were not only impaired in their behavioral performance on SORT relative to controls, but also displayed alteration in the corresponding ERPs. The altered neural activity in aMCI compared to controls suggests a more sustained and effortful search during object memory retrieval, which may be a potential marker indicating disease processes at the pre-dementia stage.

The influence of speech rate and accent on access and use of semantic information.

PubMed

Sajin, Stanislav M; Connine, Cynthia M

2017-04-01

Circumstances in which the speech input is presented in sub-optimal conditions generally lead to processing costs affecting spoken word recognition. The current study indicates that some processing demands imposed by listening to difficult speech can be mitigated by feedback from semantic knowledge. A set of lexical decision experiments examined how foreign accented speech and word duration impact access to semantic knowledge in spoken word recognition. Results indicate that when listeners process accented speech, the reliance on semantic information increases. Speech rate was not observed to influence semantic access, except in the setting in which unusually slow accented speech was presented. These findings support interactive activation models of spoken word recognition in which attention is modulated based on speech demands.

How Visual and Semantic Information Influence Learning in Familiar Contexts

ERIC Educational Resources Information Center

Goujon, Annabelle; Brockmole, James R.; Ehinger, Krista A.

2012-01-01

Previous research using the contextual cuing paradigm has revealed both quantitative and qualitative differences in learning depending on whether repeated contexts are defined by letter arrays or real-world scenes. To clarify the relative contributions of visual features and semantic information likely to account for such differences, the typical…

Computation of Semantic Number from Morphological Information

ERIC Educational Resources Information Center

Berent, Iris; Pinker, Steven; Tzelgov, Joseph; Bibi, Uri; Goldfarb, Liat

2005-01-01

The distinction between singular and plural enters into linguistic phenomena such as morphology, lexical semantics, and agreement and also must interface with perceptual and conceptual systems that assess numerosity in the world. Three experiments examine the computation of semantic number for singulars and plurals from the morphological…

Target-Oriented High-Resolution SAR Image Formation via Semantic Information Guided Regularizations

NASA Astrophysics Data System (ADS)

Hou, Biao; Wen, Zaidao; Jiao, Licheng; Wu, Qian

2018-04-01

Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.

Encoding Sequential Information in Semantic Space Models: Comparing Holographic Reduced Representation and Random Permutation

PubMed Central

Recchia, Gabriel; Sahlgren, Magnus; Kanerva, Pentti; Jones, Michael N.

2015-01-01

Circular convolution and random permutation have each been proposed as neurally plausible binding operators capable of encoding sequential information in semantic memory. We perform several controlled comparisons of circular convolution and random permutation as means of encoding paired associates as well as encoding sequential information. Random permutations outperformed convolution with respect to the number of paired associates that can be reliably stored in a single memory trace. Performance was equal on semantic tasks when using a small corpus, but random permutations were ultimately capable of achieving superior performance due to their higher scalability to large corpora. Finally, “noisy” permutations in which units are mapped to other units arbitrarily (no one-to-one mapping) perform nearly as well as true permutations. These findings increase the neurological plausibility of random permutations and highlight their utility in vector space models of semantics. PMID:25954306

SSWAP: A Simple Semantic Web Architecture and Protocol for Semantic Web Services

USDA-ARS?s Scientific Manuscript database

SSWAP (Simple Semantic Web Architecture and Protocol) is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP is the driving technology behind the Virtual Plant Information Network, an NSF-funded semantic w...

Semantic information extracting system for classification of radiological reports in radiology information system (RIS)

NASA Astrophysics Data System (ADS)

Shi, Liehang; Ling, Tonghui; Zhang, Jianguo

2016-03-01

Radiologists currently use a variety of terminologies and standards in most hospitals in China, and even there are multiple terminologies being used for different sections in one department. In this presentation, we introduce a medical semantic comprehension system (MedSCS) to extract semantic information about clinical findings and conclusion from free text radiology reports so that the reports can be classified correctly based on medical terms indexing standards such as Radlex or SONMED-CT. Our system (MedSCS) is based on both rule-based methods and statistics-based methods which improve the performance and the scalability of MedSCS. In order to evaluate the over all of the system and measure the accuracy of the outcomes, we developed computation methods to calculate the parameters of precision rate, recall rate, F-score and exact confidence interval.

Does dynamic information about the speaker's face contribute to semantic speech processing? ERP evidence.

PubMed

Hernández-Gutiérrez, David; Abdel Rahman, Rasha; Martín-Loeches, Manuel; Muñoz, Francisco; Schacht, Annekathrin; Sommer, Werner

2018-07-01

Face-to-face interactions characterize communication in social contexts. These situations are typically multimodal, requiring the integration of linguistic auditory input with facial information from the speaker. In particular, eye gaze and visual speech provide the listener with social and linguistic information, respectively. Despite the importance of this context for an ecological study of language, research on audiovisual integration has mainly focused on the phonological level, leaving aside effects on semantic comprehension. Here we used event-related potentials (ERPs) to investigate the influence of facial dynamic information on semantic processing of connected speech. Participants were presented with either a video or a still picture of the speaker, concomitant to auditory sentences. Along three experiments, we manipulated the presence or absence of the speaker's dynamic facial features (mouth and eyes) and compared the amplitudes of the semantic N400 elicited by unexpected words. Contrary to our predictions, the N400 was not modulated by dynamic facial information; therefore, semantic processing seems to be unaffected by the speaker's gaze and visual speech. Even though, during the processing of expected words, dynamic faces elicited a long-lasting late posterior positivity compared to the static condition. This effect was significantly reduced when the mouth of the speaker was covered. Our findings may indicate an increase of attentional processing to richer communicative contexts. The present findings also demonstrate that in natural communicative face-to-face encounters, perceiving the face of a speaker in motion provides supplementary information that is taken into account by the listener, especially when auditory comprehension is non-demanding. Copyright © 2018 Elsevier Ltd. All rights reserved.

Attention during natural vision warps semantic representation across the human brain.

PubMed

Çukur, Tolga; Nishimoto, Shinji; Huth, Alexander G; Gallant, Jack L

2013-06-01

Little is known about how attention changes the cortical representation of sensory information in humans. On the basis of neurophysiological evidence, we hypothesized that attention causes tuning changes to expand the representation of attended stimuli at the cost of unattended stimuli. To investigate this issue, we used functional magnetic resonance imaging to measure how semantic representation changed during visual search for different object categories in natural movies. We found that many voxels across occipito-temporal and fronto-parietal cortex shifted their tuning toward the attended category. These tuning shifts expanded the representation of the attended category and of semantically related, but unattended, categories, and compressed the representation of categories that were semantically dissimilar to the target. Attentional warping of semantic representation occurred even when the attended category was not present in the movie; thus, the effect was not a target-detection artifact. These results suggest that attention dynamically alters visual representation to optimize processing of behaviorally relevant objects during natural vision.

Attention During Natural Vision Warps Semantic Representation Across the Human Brain

PubMed Central

Çukur, Tolga; Nishimoto, Shinji; Huth, Alexander G.; Gallant, Jack L.

2013-01-01

Little is known about how attention changes the cortical representation of sensory information in humans. Based on neurophysiological evidence, we hypothesized that attention causes tuning changes to expand the representation of attended stimuli at the cost of unattended stimuli. To investigate this issue we used functional MRI (fMRI) to measure how semantic representation changes when searching for different object categories in natural movies. We find that many voxels across occipito-temporal and fronto-parietal cortex shift their tuning toward the attended category. These tuning shifts expand the representation of the attended category and of semantically-related but unattended categories, and compress the representation of categories semantically-dissimilar to the target. Attentional warping of semantic representation occurs even when the attended category is not present in the movie, thus the effect is not a target-detection artifact. These results suggest that attention dynamically alters visual representation to optimize processing of behaviorally relevant objects during natural vision. PMID:23603707

Famous face identification in temporal lobe epilepsy: Support for a multimodal integration model of semantic memory

PubMed Central

Drane, Daniel L.; Ojemann, Jeffrey G.; Phatak, Vaishali; Loring, David W.; Gross, Robert E.; Hebb, Adam O.; Silbergeld, Daniel L.; Miller, John W.; Voets, Natalie L.; Saindane, Amit M.; Barsalou, Lawrence; Meador, Kimford J.; Ojemann, George A.; Tranel, Daniel

2012-01-01

This study aims to demonstrate that the left and right anterior temporal lobes (ATLs) perform critical but unique roles in famous face identification, with damage to either leading to differing deficit patterns reflecting decreased access to lexical or semantic concepts but not their degradation. Famous face identification was studied in 22 presurgical and 14 postsurgical temporal lobe epilepsy (TLE) patients and 20 healthy comparison subjects using free recall and multiple choice (MC) paradigms. Right TLE patients exhibited presurgical deficits in famous face recognition, and postsurgical deficits in both famous face recognition and familiarity judgments. However, they did not exhibit any problems with naming before or after surgery. In contrast, left TLE patients demonstrated both pre-and postsurgical deficits in famous face naming but no significant deficits in recognition or familiarity. Double dissociations in performance between groups were alleviated by altering task demands. Postsurgical right TLE patients provided with MC options correctly identified greater than 70% of famous faces they initially rated as unfamiliar. Left TLE patients accurately chose the name for nearly all famous faces they recognized (based on their verbal description) but initially failed to name, although they tended to rapidly lose access to this name. We believe alterations in task demands activate alternative routes to semantic and lexical networks, demonstrating that unique pathways to such stored information exist, and suggesting a different role for each ATL in identifying visually presented famous faces. The right ATL appears to play a fundamental role in accessing semantic information from a visual route, with the left ATL serving to link semantic information to the language system to produce a specific name. These findings challenge several assumptions underlying amodal models of semantic memory, and provide support for the integrated multimodal theories of semantic memory

Famous face identification in temporal lobe epilepsy: support for a multimodal integration model of semantic memory.

PubMed

Drane, Daniel L; Ojemann, Jeffrey G; Phatak, Vaishali; Loring, David W; Gross, Robert E; Hebb, Adam O; Silbergeld, Daniel L; Miller, John W; Voets, Natalie L; Saindane, Amit M; Barsalou, Lawrence; Meador, Kimford J; Ojemann, George A; Tranel, Daniel

2013-06-01

This study aims to demonstrate that the left and right anterior temporal lobes (ATLs) perform critical but unique roles in famous face identification, with damage to either leading to differing deficit patterns reflecting decreased access to lexical or semantic concepts but not their degradation. Famous face identification was studied in 22 presurgical and 14 postsurgical temporal lobe epilepsy (TLE) patients and 20 healthy comparison subjects using free recall and multiple choice (MC) paradigms. Right TLE patients exhibited presurgical deficits in famous face recognition, and postsurgical deficits in both famous face recognition and familiarity judgments. However, they did not exhibit any problems with naming before or after surgery. In contrast, left TLE patients demonstrated both pre- and postsurgical deficits in famous face naming but no significant deficits in recognition or familiarity. Double dissociations in performance between groups were alleviated by altering task demands. Postsurgical right TLE patients provided with MC options correctly identified greater than 70% of famous faces they initially rated as unfamiliar. Left TLE patients accurately chose the name for nearly all famous faces they recognized (based on their verbal description) but initially failed to name, although they tended to rapidly lose access to this name. We believe alterations in task demands activate alternative routes to semantic and lexical networks, demonstrating that unique pathways to such stored information exist, and suggesting a different role for each ATL in identifying visually presented famous faces. The right ATL appears to play a fundamental role in accessing semantic information from a visual route, with the left ATL serving to link semantic information to the language system to produce a specific name. These findings challenge several assumptions underlying amodal models of semantic memory, and provide support for the integrated multimodal theories of semantic memory

Semantic segmentation of mFISH images using convolutional networks.

PubMed

Pardo, Esteban; Morgado, José Mário T; Malpica, Norberto

2018-04-30

Multicolor in situ hybridization (mFISH) is a karyotyping technique used to detect major chromosomal alterations using fluorescent probes and imaging techniques. Manual interpretation of mFISH images is a time consuming step that can be automated using machine learning; in previous works, pixel or patch wise classification was employed, overlooking spatial information which can help identify chromosomes. In this work, we propose a fully convolutional semantic segmentation network for the interpretation of mFISH images, which uses both spatial and spectral information to classify each pixel in an end-to-end fashion. The semantic segmentation network developed was tested on samples extracted from a public dataset using cross validation. Despite having no labeling information of the image it was tested on, our algorithm yielded an average correct classification ratio (CCR) of 87.41%. Previously, this level of accuracy was only achieved with state of the art algorithms when classifying pixels from the same image in which the classifier has been trained. These results provide evidence that fully convolutional semantic segmentation networks may be employed in the computer aided diagnosis of genetic diseases with improved performance over the current image analysis methods. © 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation

PubMed Central

Huang, Chung-Chi; Lu, Zhiyong

2016-01-01

Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as ‘CHEMICAL-1 compared to CHEMICAL-2.’ With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical–disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked

Semantic Information Processing of Physical Simulation Based on Scientific Concept Vocabulary Model

NASA Astrophysics Data System (ADS)

Kino, Chiaki; Suzuki, Yoshio; Takemiya, Hiroshi

Scientific Concept Vocabulary (SCV) has been developed to actualize Cognitive methodology based Data Analysis System: CDAS which supports researchers to analyze large scale data efficiently and comprehensively. SCV is an information model for processing semantic information for physics and engineering. In the model of SCV, all semantic information is related to substantial data and algorisms. Consequently, SCV enables a data analysis system to recognize the meaning of execution results output from a numerical simulation. This method has allowed a data analysis system to extract important information from a scientific view point. Previous research has shown that SCV is able to describe simple scientific indices and scientific perceptions. However, it is difficult to describe complex scientific perceptions by currently-proposed SCV. In this paper, a new data structure for SCV has been proposed in order to describe scientific perceptions in more detail. Additionally, the prototype of the new model has been constructed and applied to actual data of numerical simulation. The result means that the new SCV is able to describe more complex scientific perceptions.

The structure of semantic person memory: evidence from semantic priming in person recognition.

PubMed

Wiese, Holger

2011-11-01

This paper reviews research on the structure of semantic person memory as examined with semantic priming. In this experimental paradigm, a familiarity decision on a target face or written name is usually faster when it is preceded by a related as compared to an unrelated prime. This effect has been shown to be relatively short lived and susceptible to interfering items. Moreover, semantic priming can cross stimulus domains, such that a written name can prime a target face and vice versa. However, it remains controversial whether representations of people are stored in associative networks based on co-occurrence, or in more abstract semantic categories. In line with prominent cognitive models of face recognition, which explain semantic priming by shared semantic information between prime and target, recent research demonstrated that priming could be obtained from purely categorically related, non-associated prime/target pairs. Although strategic processes, such as expectancy and retrospective matching likely contribute, there is also evidence for a non-strategic contribution to priming, presumably related to spreading activation. Finally, a semantic priming effect has been demonstrated in the N400 event-related potential (ERP) component, which may reflect facilitated access to semantic information. It is concluded that categorical relatedness is one organizing principle of semantic person memory. ©2011 The British Psychological Society.

Dissociative Contributions of Semantic and Lexical-Phonological Information to Immediate Recognition

ERIC Educational Resources Information Center

Nishiyama, Ryoji

2013-01-01

Several neuropsychological studies have reported that patients with memory deficits exhibit a dissociation of effects attributed to semantic and lexical-phonological information in verbal working memory (e.g., Reilly, Martin, & Grossman, 2005; Romani & Martin, 1999). The present study reports on 3 experiments conducted with individuals without…

Guidance of visual attention by semantic information in real-world scenes

PubMed Central

Wu, Chia-Chien; Wick, Farahnaz Ahmed; Pomplun, Marc

2014-01-01

Recent research on attentional guidance in real-world scenes has focused on object recognition within the context of a scene. This approach has been valuable for determining some factors that drive the allocation of visual attention and determine visual selection. This article provides a review of experimental work on how different components of context, especially semantic information, affect attentional deployment. We review work from the areas of object recognition, scene perception, and visual search, highlighting recent studies examining semantic structure in real-world scenes. A better understanding on how humans parse scene representations will not only improve current models of visual attention but also advance next-generation computer vision systems and human-computer interfaces. PMID:24567724

A service-oriented distributed semantic mediator: integrating multiscale biomedical information.

PubMed

Mora, Oscar; Engelbrecht, Gerhard; Bisbal, Jesus

2012-11-01

Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.

Semantic enrichment of clinical models towards semantic interoperability. The heart failure summary use case.

PubMed

Martínez-Costa, Catalina; Cornet, Ronald; Karlsson, Daniel; Schulz, Stefan; Kalra, Dipak

2015-05-01

To improve semantic interoperability of electronic health records (EHRs) by ontology-based mediation across syntactically heterogeneous representations of the same or similar clinical information. Our approach is based on a semantic layer that consists of: (1) a set of ontologies supported by (2) a set of semantic patterns. The first aspect of the semantic layer helps standardize the clinical information modeling task and the second shields modelers from the complexity of ontology modeling. We applied this approach to heterogeneous representations of an excerpt of a heart failure summary. Using a set of finite top-level patterns to derive semantic patterns, we demonstrate that those patterns, or compositions thereof, can be used to represent information from clinical models. Homogeneous querying of the same or similar information, when represented according to heterogeneous clinical models, is feasible. Our approach focuses on the meaning embedded in EHRs, regardless of their structure. This complex task requires a clear ontological commitment (ie, agreement to consistently use the shared vocabulary within some context), together with formalization rules. These requirements are supported by semantic patterns. Other potential uses of this approach, such as clinical models validation, require further investigation. We show how an ontology-based representation of a clinical summary, guided by semantic patterns, allows homogeneous querying of heterogeneous information structures. Whether there are a finite number of top-level patterns is an open question. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Semantic integration of audio-visual information of polyphonic characters in a sentence context: an event-related potential study.

PubMed

Liu, Hong; Zhang, Gaoyan; Liu, Baolin

2017-04-01

In the Chinese language, a polyphone is a kind of special character that has more than one pronunciation, with each pronunciation corresponding to a different meaning. Here, we aimed to reveal the cognitive processing of audio-visual information integration of polyphones in a sentence context using the event-related potential (ERP) method. Sentences ending with polyphones were presented to subjects simultaneously in both an auditory and a visual modality. Four experimental conditions were set in which the visual presentations were the same, but the pronunciations of the polyphones were: the correct pronunciation; another pronunciation of the polyphone; a semantically appropriate pronunciation but not the pronunciation of the polyphone; or a semantically inappropriate pronunciation but also not the pronunciation of the polyphone. The behavioral results demonstrated significant differences in response accuracies when judging the semantic meanings of the audio-visual sentences, which reflected the different demands on cognitive resources. The ERP results showed that in the early stage, abnormal pronunciations were represented by the amplitude of the P200 component. Interestingly, because the phonological information mediated access to the lexical semantics, the amplitude and latency of the N400 component changed linearly across conditions, which may reflect the gradually increased semantic mismatch in the four conditions when integrating the auditory pronunciation with the visual information. Moreover, the amplitude of the late positive shift (LPS) showed a significant correlation with the behavioral response accuracies, demonstrating that the LPS component reveals the demand of cognitive resources for monitoring and resolving semantic conflicts when integrating the audio-visual information.

Preservation of Person-Specific Semantic Knowledge in Semantic Dementia: Does Direct Personal Experience Have a Specific Role?

PubMed Central

Péron, Julie A.; Piolino, Pascale; Moal-Boursiquot, Sandrine Le; Biseul, Isabelle; Leray, Emmanuelle; Bon, Laetitia; Desgranges, Béatrice; Eustache, Francis; Belliard, Serge

2015-01-01

Semantic dementia patients seem to have better knowledge of information linked to the self. More specifically, despite having severe semantic impairment, these patients show that they have more general information about the people they know personally by direct experience than they do about other individuals they know indirectly. However, the role of direct personal experience remains debated because of confounding factors such as frequency, recency of exposure, and affective relevance. We performed an exploratory study comparing the performance of five semantic dementia patients with that of 10 matched healthy controls on the recognition (familiarity judgment) and identification (biographic information recall) of personally familiar names vs. famous names. As expected, intergroup comparisons indicated a semantic breakdown in semantic dementia patients as compared with healthy controls. Moreover, unlike healthy controls, the semantic dementia patients recognized and identified personally familiar names better than they did famous names. This pattern of results suggests that direct personal experience indeed plays a specific role in the relative preservation of person-specific semantic meaning in semantic dementia. We discuss the role of direct personal experience on the preservation of semantic knowledge and the potential neurophysiological mechanisms underlying these processes. PMID:26635578

Altered structure-function relations of semantic processing in youths with high-functioning autism: a combined diffusion and functional MRI study.

PubMed

Lo, Yu-Chun; Chou, Tai-Li; Fan, Li-Ying; Gau, Susan Shur-Fen; Chiu, Yen-Nan; Tseng, Wen-Yih Isaac

2013-12-01

Deficits in language and communication are among the core symptoms of autism, a common neurodevelopmental disorder with long-term impairment. Despite the striking nature of the autistic language impairment, knowledge about its corresponding alterations in the brain is still evolving. We hypothesized that the dual stream language network is altered in autism, and that this alteration could be revealed by changes in the relationships between microstructural integrity and functional activation. The study recruited 20 right-handed male youths with autism and 20 carefully matched individually, typically developing (TD) youths. Microstructural integrity of the left dorsal and left ventral pathways responsible for language processing and the functional activation of the connected brain regions were investigated by using diffusion spectrum imaging and functional magnetic resonance imaging of a semantic task, respectively. Youths with autism had significantly poorer language function, and lower functional activation in left dorsal and left ventral regions of the language network, compared with TD youths. The TD group showed a significant correlation of the functional activation of the left dorsal region with microstructural integrity of the left ventral pathway, whereas the autism group showed a significant correlation of the functional activation of the left ventral region with microstructural integrity of the left dorsal pathway, and moreover verbal comprehension index was correlated with microstructural integrity of the left ventral pathway. These altered structure-function relationships in autism suggest possible involvement of the dual pathways in supporting deficient semantic processing. © 2013 International Society for Autism Research, Wiley Periodicals, Inc.

Mandarin-Speaking Children's Speech Recognition: Developmental Changes in the Influences of Semantic Context and F0 Contours.

PubMed

Zhou, Hong; Li, Yu; Liang, Meng; Guan, Connie Qun; Zhang, Linjun; Shu, Hua; Zhang, Yang

2017-01-01

The goal of this developmental speech perception study was to assess whether and how age group modulated the influences of high-level semantic context and low-level fundamental frequency ( F 0 ) contours on the recognition of Mandarin speech by elementary and middle-school-aged children in quiet and interference backgrounds. The results revealed different patterns for semantic and F 0 information. One the one hand, age group modulated significantly the use of F 0 contours, indicating that elementary school children relied more on natural F 0 contours than middle school children during Mandarin speech recognition. On the other hand, there was no significant modulation effect of age group on semantic context, indicating that children of both age groups used semantic context to assist speech recognition to a similar extent. Furthermore, the significant modulation effect of age group on the interaction between F 0 contours and semantic context revealed that younger children could not make better use of semantic context in recognizing speech with flat F 0 contours compared with natural F 0 contours, while older children could benefit from semantic context even when natural F 0 contours were altered, thus confirming the important role of F 0 contours in Mandarin speech recognition by elementary school children. The developmental changes in the effects of high-level semantic and low-level F 0 information on speech recognition might reflect the differences in auditory and cognitive resources associated with processing of the two types of information in speech perception.

Processing of Formational, Semantic, and Iconic Information in American Sign Language.

ERIC Educational Resources Information Center

Poizner, Howard; And Others

1981-01-01

Three experiments examined short-term encoding processes of deaf signers for different aspects of signs from American Sign Language. Results indicated that deaf signers code signs at one level in terms of linguistically significant formational parameters. The semantic and iconic information of signs, however, has little effect on short-term…

Context-based tourism information filtering with a semantic rule engine.

PubMed

Lamsfus, Carlos; Martin, David; Alzua-Sorzabal, Aurkene; López-de-Ipiña, Diego; Torres-Manzanera, Emilio

2012-01-01

This paper presents the CONCERT framework, a push/filter information consumption paradigm, based on a rule-based semantic contextual information system for tourism. CONCERT suggests a specific insight of the notion of context from a human mobility perspective. It focuses on the particular characteristics and requirements of travellers and addresses the drawbacks found in other approaches. Additionally, CONCERT suggests the use of digital broadcasting as push communication technology, whereby tourism information is disseminated to mobile devices. This information is then automatically filtered by a network of ontologies and offered to tourists on the screen. The results obtained in the experiments carried out show evidence that the information disseminated through digital broadcasting can be manipulated by the network of ontologies, providing contextualized information that produces user satisfaction.

Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

PubMed

Gladun, Anatoly; Rogushina, Julia; Valencia-García, Rafael; Béjar, Rodrigo Martínez

2013-03-01

A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation.

PubMed

Huang, Chung-Chi; Lu, Zhiyong

2016-01-01

Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order

Enhancing acronym/abbreviation knowledge bases with semantic information.

PubMed

Torii, Manabu; Liu, Hongfang

2007-10-11

In the biomedical domain, a terminology knowledge base that associates acronyms/abbreviations (denoted as SFs) with the definitions (denoted as LFs) is highly needed. For the construction such terminology knowledge base, we investigate the feasibility to build a system automatically assigning semantic categories to LFs extracted from text. Given a collection of pairs (SF,LF) derived from text, we i) assess the coverage of LFs and pairs (SF,LF) in the UMLS and justify the need of a semantic category assignment system; and ii) automatically derive name phrases annotated with semantic category and construct a system using machine learning. Utilizing ADAM, an existing collection of (SF,LF) pairs extracted from MEDLINE, our system achieved an f-measure of 87% when assigning eight UMLS-based semantic groups to LFs. The system has been incorporated into a web interface which integrates SF knowledge from multiple SF knowledge bases. Web site: http://gauss.dbb.georgetown.edu/liblab/SFThesurus.

An ERP study on whether semantic integration exists in processing ecologically unrelated audio-visual information.

PubMed

Liu, Baolin; Meng, Xianyao; Wang, Zhongning; Wu, Guangning

2011-11-14

In the present study, we used event-related potentials (ERPs) to examine whether semantic integration occurs for ecologically unrelated audio-visual information. Videos with synchronous audio-visual information were used as stimuli, where the auditory stimuli were sine wave sounds with different sound levels, and the visual stimuli were simple geometric figures with different areas. In the experiment, participants were shown an initial display containing a single shape (drawn from a set of 6 shapes) with a fixed size (14cm(2)) simultaneously with a 3500Hz tone of a fixed intensity (80dB). Following a short delay, another shape/tone pair was presented and the relationship between the size of the shape and the intensity of the tone varied across trials: in the V+A- condition, a large shape was paired with a soft tone; in the V+A+ condition, a large shape was paired with a loud tone, and so forth. The ERPs results revealed that N400 effect was elicited under the VA- condition (V+A- and V-A+) as compared to the VA+ condition (V+A+ and V-A-). It was shown that semantic integration would occur when simultaneous, ecologically unrelated auditory and visual stimuli enter the human brain. We considered that this semantic integration was based on semantic constraint of audio-visual information, which might come from the long-term learned association stored in the human brain and short-term experience of incoming information. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Towards A Topological Framework for Integrating Semantic Information Sources

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

Joslyn, Cliff A.; Hogan, Emilie A.; Robinson, Michael

2014-09-07

In this position paper we argue for the role that topological modeling principles can play in providing a framework for sensor integration. While used successfully in standard (quantitative) sensors, we are developing this methodology in new directions to make it appropriate specifically for semantic information sources, including keyterms, ontology terms, and other general Boolean, categorical, ordinal, and partially-ordered data types. We illustrate the basics of the methodology in an extended use case/example, and discuss path forward.

Processing Lexical and Speaker Information in Repetition and Semantic/Associative Priming

ERIC Educational Resources Information Center

Lee, Chao-Yang; Zhang, Yu

2018-01-01

The purpose of this study is to investigate the interaction between processing lexical and speaker-specific information in spoken word recognition. The specific question is whether repetition and semantic/associative priming is reduced when the prime and target are produced by different speakers. In Experiment 1, the prime and target were repeated…

I See What You Mean: Theta Power Increases Are Involved in the Retrieval of Lexical Semantic Information

ERIC Educational Resources Information Center

Bastiaansen, Marcel C. M.; Oostenveld, Robert; Jensen, Ole; Hagoort, Peter

2008-01-01

An influential hypothesis regarding the neural basis of the mental lexicon is that semantic representations are neurally implemented as distributed networks carrying sensory, motor and/or more abstract functional information. This work investigates whether the semantic properties of words partly determine the topography of such networks. Subjects…

Only time will tell - why temporal information is essential for our neuroscientific understanding of semantics.

PubMed

Hauk, Olaf

2016-08-01

Theoretical developments about the nature of semantic representations and processes should be accompanied by a discussion of how these theories can be validated on the basis of empirical data. Here, I elaborate on the link between theory and empirical research, highlighting the need for temporal information in order to distinguish fundamental aspects of semantics. The generic point that fast cognitive processes demand fast measurement techniques has been made many times before, although arguably more often in the psychophysiological community than in the metabolic neuroimaging community. Many reviews on the neuroscience of semantics mostly or even exclusively focus on metabolic neuroimaging data. Following an analysis of semantics in terms of the representations and processes involved, I argue that fundamental theoretical debates about the neuroscience of semantics can only be concluded on the basis of data with sufficient temporal resolution. Any "semantic effect" may result from a conflation of long-term memory representations, retrieval and working memory processes, mental imagery, and episodic memory. This poses challenges for all neuroimaging modalities, but especially for those with low temporal resolution. It also throws doubt on the usefulness of contrasts between meaningful and meaningless stimuli, which may differ on a number of semantic and non-semantic dimensions. I will discuss the consequences of this analysis for research on the role of convergence zones or hubs and distributed modal brain networks, top-down modulation of task and context as well as interactivity between levels of the processing hierarchy, for example in the framework of predictive coding.

Context-Based Tourism Information Filtering with a Semantic Rule Engine

PubMed Central

Lamsfus, Carlos; Martin, David; Alzua-Sorzabal, Aurkene; López-de-Ipiña, Diego; Torres-Manzanera, Emilio

2012-01-01

This paper presents the CONCERT framework, a push/filter information consumption paradigm, based on a rule-based semantic contextual information system for tourism. CONCERT suggests a specific insight of the notion of context from a human mobility perspective. It focuses on the particular characteristics and requirements of travellers and addresses the drawbacks found in other approaches. Additionally, CONCERT suggests the use of digital broadcasting as push communication technology, whereby tourism information is disseminated to mobile devices. This information is then automatically filtered by a network of ontologies and offered to tourists on the screen. The results obtained in the experiments carried out show evidence that the information disseminated through digital broadcasting can be manipulated by the network of ontologies, providing contextualized information that produces user satisfaction. PMID:22778584

Adventures in Semantic Publishing: Exemplar Semantic Enhancements of a Research Article

PubMed Central

Shotton, David; Portwin, Katie; Klyne, Graham; Miles, Alistair

2009-01-01

Scientific innovation depends on finding, integrating, and re-using the products of previous research. Here we explore how recent developments in Web technology, particularly those related to the publication of data and metadata, might assist that process by providing semantic enhancements to journal articles within the mainstream process of scholarly journal publishing. We exemplify this by describing semantic enhancements we have made to a recent biomedical research article taken from PLoS Neglected Tropical Diseases, providing enrichment to its content and increased access to datasets within it. These semantic enhancements include provision of live DOIs and hyperlinks; semantic markup of textual terms, with links to relevant third-party information resources; interactive figures; a re-orderable reference list; a document summary containing a study summary, a tag cloud, and a citation analysis; and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit “Citations in Context”, and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups) with results from other research articles and with Google Maps. We have also published machine-readable RDF metadata both about the article and about the references it cites, for which we developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/). The enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a compelling existence proof of the possibilities of semantic publication. We hope the showcase of examples and ideas it contains, described in this paper, will excite the imaginations of researchers and publishers, stimulating them to explore the possibilities of semantic publishing for their own research

Mediator infrastructure for information integration and semantic data integration environment for biomedical research.

PubMed

Grethe, Jeffrey S; Ross, Edward; Little, David; Sanders, Brian; Gupta, Amarnath; Astakhov, Vadim

2009-01-01

This paper presents current progress in the development of semantic data integration environment which is a part of the Biomedical Informatics Research Network (BIRN; http://www.nbirn.net) project. BIRN is sponsored by the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). A goal is the development of a cyberinfrastructure for biomedical research that supports advance data acquisition, data storage, data management, data integration, data mining, data visualization, and other computing and information processing services over the Internet. Each participating institution maintains storage of their experimental or computationally derived data. Mediator-based data integration system performs semantic integration over the databases to enable researchers to perform analyses based on larger and broader datasets than would be available from any single institution's data. This paper describes recent revision of the system architecture, implementation, and capabilities of the semantically based data integration environment for BIRN.

Supporting Information Linking and Discovery Across Organizations Using the VIVO Semantic Web Software Suite

NASA Astrophysics Data System (ADS)

Mayernik, M. S.; Daniels, M. D.; Maull, K. E.; Khan, H.; Krafft, D. B.; Gross, M. B.; Rowan, L. R.

2016-12-01

Geosciences research is often conducted using distributed networks of researchers and resources. To better enable the discovery of the research output from the scientists and resources used within these organizations, UCAR, Cornell University, and UNAVCO are collaborating on the EarthCollab (http://earthcube.org/group/earthcollab) project which seeks to leverage semantic technologies to manage and link scientific data. As part of this effort, we have been exploring how to leverage information distributed across multiple research organizations. EarthCollab is using the VIVO semantic software suite to lookup and display Semantic Web information across our project partners.Our presentation will include a demonstration of linking between VIVO instances, discussing how to create linkages between entities in different VIVO instances where both entities describe the same person or resource. This discussion will explore how we designate the equivalence of these entities using "same as" assertions between identifiers representing these entities including URIs and ORCID IDs and how we have extended the base VIVO architecture to support the lookup of which entities in separate VIVO instances may be equivalent and to then display information from external linked entities. We will also discuss how these extensions can support other linked data lookups and sources of information.This VIVO cross-linking mechanism helps bring information from multiple VIVO instances together and helps users in navigating information spread-out between multiple VIVO instances. Challenges and open questions for this approach relate to how to display the information obtained from an external VIVO instance, both in order to preserve the brands of the internal and external systems and to handle discrepancies between ontologies, content, and/or VIVO versions.

SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Berrios, Daniel C.; Carvalho, Robert E.; Hall, David R.; Rich, Stephen J.; Sturken, Ian B.; Swanson, Keith J.; Wolfe, Shawn R.

2004-01-01

SemanticOrganizer is a collaborative knowledge management system designed to support distributed NASA projects, including diverse teams of scientists, engineers, and accident investigators. The system provides a customizable, semantically structured information repository that stores work products relevant to multiple projects of differing types. SemanticOrganizer is one of the earliest and largest semantic web applications deployed at NASA to date, and has been used in diverse contexts ranging from the investigation of Space Shuttle Columbia's accident to the search for life on other planets. Although the underlying repository employs a single unified ontology, access control and ontology customization mechanisms make the repository contents appear different for each project team. This paper describes SemanticOrganizer, its customization facilities, and a sampling of its applications. The paper also summarizes some key lessons learned from building and fielding a successful semantic web application across a wide-ranging set of domains with diverse users.

Semantically Interoperable XML Data

PubMed Central

Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

2013-01-01

XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups. PMID:25298789

Social Semantics for an Effective Enterprise

NASA Technical Reports Server (NTRS)

Berndt, Sarah; Doane, Mike

2012-01-01

An evolution of the Semantic Web, the Social Semantic Web (s2w), facilitates knowledge sharing with "useful information based on human contributions, which gets better as more people participate." The s2w reaches beyond the search box to move us from a collection of hyperlinked facts, to meaningful, real time context. When focused through the lens of Enterprise Search, the Social Semantic Web facilitates the fluid transition of meaningful business information from the source to the user. It is the confluence of human thought and computer processing structured with the iterative application of taxonomies, folksonomies, ontologies, and metadata schemas. The importance and nuances of human interaction are often deemphasized when focusing on automatic generation of semantic markup, which results in dissatisfied users and unrealized return on investment. Users consistently qualify the value of information sets through the act of selection, making them the de facto stakeholders of the Social Semantic Web. Employers are the ultimate beneficiaries of s2w utilization with a better informed, more decisive workforce; one not achieved with an IT miracle technology, but by improved human-computer interactions. Johnson Space Center Taxonomist Sarah Berndt and Mike Doane, principal owner of Term Management, LLC discuss the planning, development, and maintenance stages for components of a semantic system while emphasizing the necessity of a Social Semantic Web for the Enterprise. Identification of risks and variables associated with layering the successful implementation of a semantic system are also modeled.

Introduction to geospatial semantics and technology workshop handbook

USGS Publications Warehouse

Varanka, Dalia E.

2012-01-01

The workshop is a tutorial on introductory geospatial semantics with hands-on exercises using standard Web browsers. The workshop is divided into two sections, general semantics on the Web and specific examples of geospatial semantics using data from The National Map of the U.S. Geological Survey and the Open Ontology Repository. The general semantics section includes information and access to publicly available semantic archives. The specific session includes information on geospatial semantics with access to semantically enhanced data for hydrography, transportation, boundaries, and names. The Open Ontology Repository offers open-source ontologies for public use.

Modulation of the inter-hemispheric processing of semantic information during normal aging. A divided visual field experiment.

PubMed

Hoyau, E; Cousin, E; Jaillard, A; Baciu, M

2016-12-01

We evaluated the effect of normal aging on the inter-hemispheric processing of semantic information by using the divided visual field (DVF) method, with words and pictures. Two main theoretical models have been considered, (a) the HAROLD model which posits that aging is associated with supplementary recruitment of the right hemisphere (RH) and decreased hemispheric specialization, and (b) the RH decline theory, which assumes that the RH becomes less efficient with aging, associated with increased LH specialization. Two groups of subjects were examined, a Young Group (YG) and an Old Group (OG), while participants performed a semantic categorization task (living vs. non-living) in words and pictures. The DVF was realized in two steps: (a) unilateral DVF presentation with stimuli presented separately in each visual field, left or right, allowing for their initial processing by only one hemisphere, right or left, respectively; (b) bilateral DVF presentation (BVF) with stimuli presented simultaneously in both visual fields, followed by their processing by both hemispheres. These two types of presentation permitted the evaluation of two main characteristics of the inter-hemispheric processing of information, the hemispheric specialization (HS) and the inter-hemispheric cooperation (IHC). Moreover, the BVF allowed determining the driver-hemisphere for processing information presented in BVF. Results obtained in OG indicated that: (a) semantic categorization was performed as accurately as YG, even if more slowly, (b) a non-semantic RH decline was observed, and (c) the LH controls the semantic processing during the BVF, suggesting an increased role of the LH in aging. However, despite the stronger involvement of the LH in OG, the RH is not completely devoid of semantic abilities. As discussed in the paper, neither the HAROLD nor the RH decline does fully explain this pattern of results. We rather suggest that the effect of aging on the hemispheric specialization and inter

Making Semantic Information Work Effectively for Degraded Environments

DTIC Science & Technology

2013-06-01

Control Research & Technology Symposium (ICCRTS) held 19-21 June, 2013 in Alexandria, VA. 14. ABSTRACT The challenges of effectively managing semantic...technologies over disadvantaged or degraded environments are numerous and complex. One of the greatest challenges is the size of raw data. Large...approach mitigates this challenge by performing data reduction through the adoption of format recognition technologies, semantic data extractions, and the

Modeling of cell signaling pathways in macrophages by semantic networks

PubMed Central

Hsing, Michael; Bellenson, Joel L; Shankey, Conor; Cherkasov, Artem

2004-01-01

Background Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. Results We have applied a semantic network (SN) approach to develop and implement a model for cell signaling pathways. The semantic model has mapped biological concepts to a set of semantic agents and relationships, and characterized cell signaling events and their participants in the hierarchical and spatial context. In particular, the available information on the behaviors and interactions of the PI3K enzyme family has been integrated into the SN environment and a cell signaling network in human macrophages has been constructed. A SN-application has been developed to manipulate the locations and the states of molecules and to observe their actions under different biological scenarios. The approach allowed qualitative simulation of cell signaling events involving PI3Ks and identified pathways of molecular interactions that led to known cellular responses as well as other potential responses during bacterial invasions in macrophages. Conclusions We concluded from our results that the semantic network is an effective method to model cell signaling pathways. The semantic model allows proper representation and integration of information on biological structures and their interactions at different levels. The reconstruction of the cell signaling network in the macrophage allowed detailed

Does the speaker matter? Online processing of semantic and pragmatic information in L2 speech comprehension.

PubMed

Foucart, Alice; Garcia, Xavier; Ayguasanosa, Meritxell; Thierry, Guillaume; Martin, Clara; Costa, Albert

2015-08-01

The present study investigated how pragmatic information is integrated during L2 sentence comprehension. We put forward that the differences often observed between L1 and L2 sentence processing may reflect differences on how various types of information are used to process a sentence, and not necessarily differences between native and non-native linguistic systems. Based on the idea that when a cue is missing or distorted, one relies more on other cues available, we hypothesised that late bilinguals favour the cues that they master during sentence processing. To verify this hypothesis we investigated whether late bilinguals take the speaker's identity (inferred by the voice) into account when incrementally processing speech and whether this affects their online interpretation of the sentence. To do so, we adapted Van Berkum, J.J.A., Van den Brink, D., Tesink, C.M.J.Y., Kos, M., Hagoort, P., 2008. J. Cogn. Neurosci. 20(4), 580-591, study in which sentences with either semantic violations or pragmatic inconsistencies were presented. While both the native and the non-native groups showed a similar response to semantic violations (N400), their response to speakers' inconsistencies slightly diverged; late bilinguals showed a positivity much earlier than native speakers (LPP). These results suggest that, like native speakers, late bilinguals process semantic and pragmatic information incrementally; however, what seems to differ between L1 and L2 processing is the time-course of the different processes. We propose that this difference may originate from late bilinguals' sensitivity to pragmatic information and/or their ability to efficiently make use of the information provided by the sentence context to generate expectations in relation to pragmatic information during L2 sentence comprehension. In other words, late bilinguals may rely more on speaker identity than native speakers when they face semantic integration difficulties. Copyright © 2015 Elsevier Ltd. All rights

Semantic information mediates visual attention during spoken word recognition in Chinese: Evidence from the printed-word version of the visual-world paradigm.

PubMed

Shen, Wei; Qu, Qingqing; Li, Xingshan

2016-07-01

In the present study, we investigated whether the activation of semantic information during spoken word recognition can mediate visual attention's deployment to printed Chinese words. We used a visual-world paradigm with printed words, in which participants listened to a spoken target word embedded in a neutral spoken sentence while looking at a visual display of printed words. We examined whether a semantic competitor effect could be observed in the printed-word version of the visual-world paradigm. In Experiment 1, the relationship between the spoken target words and the printed words was manipulated so that they were semantically related (a semantic competitor), phonologically related (a phonological competitor), or unrelated (distractors). We found that the probability of fixations on semantic competitors was significantly higher than that of fixations on the distractors. In Experiment 2, the orthographic similarity between the spoken target words and their semantic competitors was manipulated to further examine whether the semantic competitor effect was modulated by orthographic similarity. We found significant semantic competitor effects regardless of orthographic similarity. Our study not only reveals that semantic information can affect visual attention, it also provides important new insights into the methodology employed to investigate the semantic processing of spoken words during spoken word recognition using the printed-word version of the visual-world paradigm.

Semantics-informed geological maps: Conceptual modeling and knowledge encoding

NASA Astrophysics Data System (ADS)

Lombardo, Vincenzo; Piana, Fabrizio; Mimmo, Dario

2018-07-01

This paper introduces a novel, semantics-informed geologic mapping process, whose application domain is the production of a synthetic geologic map of a large administrative region. A number of approaches concerning the expression of geologic knowledge through UML schemata and ontologies have been around for more than a decade. These approaches have yielded resources that concern specific domains, such as, e.g., lithology. We develop a conceptual model that aims at building a digital encoding of several domains of geologic knowledge, in order to support the interoperability of the sources. We apply the devised terminological base to the classification of the elements of a geologic map of the Italian Western Alps and northern Apennines (Piemonte region). The digitally encoded knowledge base is a merged set of ontologies, called OntoGeonous. The encoding process identifies the objects of the semantic encoding, the geologic units, gathers the relevant information about such objects from authoritative resources, such as GeoSciML (giving priority to the application schemata reported in the INSPIRE Encoding Cookbook), and expresses the statements by means of axioms encoded in the Web Ontology Language (OWL). To support interoperability, OntoGeonous interlinks the general concepts by referring to the upper part level of ontology SWEET (developed by NASA), and imports knowledge that is already encoded in ontological format (e.g., ontology Simple Lithology). Machine-readable knowledge allows for consistency checking and for classification of the geological map data through algorithms of automatic reasoning.

Parafoveal processing in silent and oral reading: Reading mode influences the relative weighting of phonological and semantic information in Chinese.

PubMed

Pan, Jinger; Laubrock, Jochen; Yan, Ming

2016-08-01

We examined how reading mode (i.e., silent vs. oral reading) influences parafoveal semantic and phonological processing during the reading of Chinese sentences, using the gaze-contingent boundary paradigm. In silent reading, we found in 2 experiments that reading times on target words were shortened with semantic previews in early and late processing, whereas phonological preview effects mainly occurred in gaze duration or second-pass reading. In contrast, results showed that phonological preview information is obtained early on in oral reading. Strikingly, in oral reading, we observed a semantic preview cost on the target word in Experiment 1 and a decrease in the effect size of preview benefit from first- to second-pass measures in Experiment 2, which we hypothesize to result from increased preview duration. Taken together, our results indicate that parafoveal semantic information can be obtained irrespective of reading mode, whereas readers more efficiently process parafoveal phonological information in oral reading. We discuss implications for notions of information processing priority and saccade generation during silent and oral reading. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Semantic attributes based texture generation

NASA Astrophysics Data System (ADS)

Chi, Huifang; Gan, Yanhai; Qi, Lin; Dong, Junyu; Madessa, Amanuel Hirpa

2018-04-01

Semantic attributes are commonly used for texture description. They can be used to describe the information of a texture, such as patterns, textons, distributions, brightness, and so on. Generally speaking, semantic attributes are more concrete descriptors than perceptual features. Therefore, it is practical to generate texture images from semantic attributes. In this paper, we propose to generate high-quality texture images from semantic attributes. Over the last two decades, several works have been done on texture synthesis and generation. Most of them focusing on example-based texture synthesis and procedural texture generation. Semantic attributes based texture generation still deserves more devotion. Gan et al. proposed a useful joint model for perception driven texture generation. However, perceptual features are nonobjective spatial statistics used by humans to distinguish different textures in pre-attentive situations. To give more describing information about texture appearance, semantic attributes which are more in line with human description habits are desired. In this paper, we use sigmoid cross entropy loss in an auxiliary model to provide enough information for a generator. Consequently, the discriminator is released from the relatively intractable mission of figuring out the joint distribution of condition vectors and samples. To demonstrate the validity of our method, we compare our method to Gan et al.'s method on generating textures by designing experiments on PTD and DTD. All experimental results show that our model can generate textures from semantic attributes.

Temporal Representation in Semantic Graphs

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

Levandoski, J J; Abdulla, G M

2007-08-07

A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts. Most of the semantic graphs used in these applications are assumed to be static pieces of information, meaning temporal evolution of concepts and relationships are not taken into account. Guided by the need for more advanced semantic graph queries involving temporal concepts, this paper surveys the existing work involving temporal representations in semantic graphs.

Integrating Semantic Information in Metadata Descriptions for a Geoscience-wide Resource Inventory.

NASA Astrophysics Data System (ADS)

Zaslavsky, I.; Richard, S. M.; Gupta, A.; Valentine, D.; Whitenack, T.; Ozyurt, I. B.; Grethe, J. S.; Schachne, A.

2016-12-01

Integrating semantic information into legacy metadata catalogs is a challenging issue and so far has been mostly done on a limited scale. We present experience of CINERGI (Community Inventory of Earthcube Resources for Geoscience Interoperability), an NSF Earthcube Building Block project, in creating a large cross-disciplinary catalog of geoscience information resources to enable cross-domain discovery. The project developed a pipeline for automatically augmenting resource metadata, in particular generating keywords that describe metadata documents harvested from multiple geoscience information repositories or contributed by geoscientists through various channels including surveys and domain resource inventories. The pipeline examines available metadata descriptions using text parsing, vocabulary management and semantic annotation and graph navigation services of GeoSciGraph. GeoSciGraph, in turn, relies on a large cross-domain ontology of geoscience terms, which bridges several independently developed ontologies or taxonomies including SWEET, ENVO, YAGO, GeoSciML, GCMD, SWO, and CHEBI. The ontology content enables automatic extraction of keywords reflecting science domains, equipment used, geospatial features, measured properties, methods, processes, etc. We specifically focus on issues of cross-domain geoscience ontology creation, resolving several types of semantic conflicts among component ontologies or vocabularies, and constructing and managing facets for improved data discovery and navigation. The ontology and keyword generation rules are iteratively improved as pipeline results are presented to data managers for selective manual curation via a CINERGI Annotator user interface. We present lessons learned from applying CINERGI metadata augmentation pipeline to a number of federal agency and academic data registries, in the context of several use cases that require data discovery and integration across multiple earth science data catalogs of varying quality

On2broker: Semantic-Based Access to Information Sources at the WWW.

ERIC Educational Resources Information Center

Fensel, Dieter; Angele, Jurgen; Decker, Stefan; Erdmann, Michael; Schnurr, Hans-Peter; Staab, Steffen; Studer, Rudi; Witt, Andreas

On2broker provides brokering services to improve access to heterogeneous, distributed, and semistructured information sources as they are presented in the World Wide Web. It relies on the use of ontologies to make explicit the semantics of Web pages. This paper discusses the general architecture and main components (i.e., query engine, information…

Examining lateralized semantic access using pictures.

PubMed

Lovseth, Kyle; Atchley, Ruth Ann

2010-03-01

A divided visual field (DVF) experiment examined the semantic processing strategies employed by the cerebral hemispheres to determine if strategies observed with written word stimuli generalize to other media for communicating semantic information. We employed picture stimuli and vary the degree of semantic relatedness between the picture pairs. Participants made an on-line semantic relatedness judgment in response to sequentially presented pictures. We found that when pictures are presented to the right hemisphere responses are generally more accurate than the left hemisphere for semantic relatedness judgments for picture pairs. Furthermore, consistent with earlier DVF studies employing words, we conclude that the RH is better at accessing or maintaining access to information that has a weak or more remote semantic relationship. We also found evidence of faster access for pictures presented to the LH in the strongly-related condition. Overall, these results are consistent with earlier DVF word studies that argue that the cerebral hemispheres each play an important and separable role during semantic retrieval. Copyright 2009 Elsevier Inc. All rights reserved.

LEARNING SEMANTICS-ENHANCED LANGUAGE MODELS APPLIED TO UNSUEPRVISED WSD

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

VERSPOOR, KARIN; LIN, SHOU-DE

An N-gram language model aims at capturing statistical syntactic word order information from corpora. Although the concept of language models has been applied extensively to handle a variety of NLP problems with reasonable success, the standard model does not incorporate semantic information, and consequently limits its applicability to semantic problems such as word sense disambiguation. We propose a framework that integrates semantic information into the language model schema, allowing a system to exploit both syntactic and semantic information to address NLP problems. Furthermore, acknowledging the limited availability of semantically annotated data, we discuss how the proposed model can be learnedmore » without annotated training examples. Finally, we report on a case study showing how the semantics-enhanced language model can be applied to unsupervised word sense disambiguation with promising results.« less

Workspaces in the Semantic Web

NASA Technical Reports Server (NTRS)

Wolfe, Shawn R.; Keller, RIchard M.

2005-01-01

Due to the recency and relatively limited adoption of Semantic Web technologies. practical issues related to technology scaling have received less attention than foundational issues. Nonetheless, these issues must be addressed if the Semantic Web is to realize its full potential. In particular, we concentrate on the lack of scoping methods that reduce the size of semantic information spaces so they are more efficient to work with and more relevant to an agent's needs. We provide some intuition to motivate the need for such reduced information spaces, called workspaces, give a formal definition, and suggest possible methods of deriving them.

Sleep Benefits Memory for Semantic Category Structure While Preserving Exemplar-Specific Information.

PubMed

Schapiro, Anna C; McDevitt, Elizabeth A; Chen, Lang; Norman, Kenneth A; Mednick, Sara C; Rogers, Timothy T

2017-11-01

Semantic memory encompasses knowledge about both the properties that typify concepts (e.g. robins, like all birds, have wings) as well as the properties that individuate conceptually related items (e.g. robins, in particular, have red breasts). We investigate the impact of sleep on new semantic learning using a property inference task in which both kinds of information are initially acquired equally well. Participants learned about three categories of novel objects possessing some properties that were shared among category exemplars and others that were unique to an exemplar, with exposure frequency varying across categories. In Experiment 1, memory for shared properties improved and memory for unique properties was preserved across a night of sleep, while memory for both feature types declined over a day awake. In Experiment 2, memory for shared properties improved across a nap, but only for the lower-frequency category, suggesting a prioritization of weakly learned information early in a sleep period. The increase was significantly correlated with amount of REM, but was also observed in participants who did not enter REM, suggesting involvement of both REM and NREM sleep. The results provide the first evidence that sleep improves memory for the shared structure of object categories, while simultaneously preserving object-unique information.

Examining Lateralized Semantic Access Using Pictures

ERIC Educational Resources Information Center

Lovseth, Kyle; Atchley, Ruth Ann

2010-01-01

A divided visual field (DVF) experiment examined the semantic processing strategies employed by the cerebral hemispheres to determine if strategies observed with written word stimuli generalize to other media for communicating semantic information. We employed picture stimuli and vary the degree of semantic relatedness between the picture pairs.…

Partial sleep deprivation does not alter processes involved in semantic word priming: event-related potential evidence.

PubMed

Tavakoli, Paniz; Muller-Gass, Alexandra; Campbell, Kenneth

2015-03-01

Sleep deprivation has generally been observed to have a detrimental effect on tasks that require sustained attention for successful performance. It might however be possible to counter these effects by altering cognitive strategies. A recent semantic word priming study indicated that subjects used an effortful predictive-expectancy search of semantic memory following normal sleep, but changed to an automatic, effortless strategy following total sleep deprivation. Partial sleep deprivation occurs much more frequently than total sleep deprivation. The present study therefore employed a similar priming task following either 4h of sleep or following normal sleep. The purpose of the study was to determine whether partial sleep deprivation would also lead to a shift in cognitive strategy to compensate for an inability to sustain attention and effortful processing necessary for using the predicative expectancy strategy. Sixteen subjects were presented with word pairs, a prime and a target that were either strongly semantically associated (cat...dog), weakly associated (cow...barn) or not associated (apple...road). The subject's task was to determine if the target word was semantically associated to the prime. A strong priming effect was observed in both conditions. RTs were slower, accuracy lower, and N400 larger to unassociated targets, independent of the amount of sleep. The overall N400 did not differ as a function of sleep. The scalp distribution of the N400 was also similar following both normal sleep and sleep loss. There was thus little evidence of a difference in the processing of the target stimulus as a function of the amount sleep. Similarly, ERPs in the period between the onset of the prime and the subsequent target also did not differ between the normal sleep and sleep loss conditions. In contrast to total sleep deprivation, subjects therefore appeared to use a common predictive expectancy strategy in both conditions. This strategy does however require an

A extract method of mountainous area settlement place information from GF-1 high resolution optical remote sensing image under semantic constraints

NASA Astrophysics Data System (ADS)

Guo, H., II

2016-12-01

Spatial distribution information of mountainous area settlement place is of great significance to the earthquake emergency work because most of the key earthquake hazardous areas of china are located in the mountainous area. Remote sensing has the advantages of large coverage and low cost, it is an important way to obtain the spatial distribution information of mountainous area settlement place. At present, fully considering the geometric information, spectral information and texture information, most studies have applied object-oriented methods to extract settlement place information, In this article, semantic constraints is to be added on the basis of object-oriented methods. The experimental data is one scene remote sensing image of domestic high resolution satellite (simply as GF-1), with a resolution of 2 meters. The main processing consists of 3 steps, the first is pretreatment, including ortho rectification and image fusion, the second is Object oriented information extraction, including Image segmentation and information extraction, the last step is removing the error elements under semantic constraints, in order to formulate these semantic constraints, the distribution characteristics of mountainous area settlement place must be analyzed and the spatial logic relation between settlement place and other objects must be considered. The extraction accuracy calculation result shows that the extraction accuracy of object oriented method is 49% and rise up to 86% after the use of semantic constraints. As can be seen from the extraction accuracy, the extract method under semantic constraints can effectively improve the accuracy of mountainous area settlement place information extraction. The result shows that it is feasible to extract mountainous area settlement place information form GF-1 image, so the article proves that it has a certain practicality to use domestic high resolution optical remote sensing image in earthquake emergency preparedness.

Semantic framework for mapping object-oriented model to semantic web languages

PubMed Central

Ježek, Petr; Mouček, Roman

2015-01-01

The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework. PMID:25762923

Semantic framework for mapping object-oriented model to semantic web languages.

PubMed

Ježek, Petr; Mouček, Roman

2015-01-01

The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.

Towards Semantic e-Science for Traditional Chinese Medicine

PubMed Central

Chen, Huajun; Mao, Yuxin; Zheng, Xiaoqing; Cui, Meng; Feng, Yi; Deng, Shuiguang; Yin, Aining; Zhou, Chunying; Tang, Jinming; Jiang, Xiaohong; Wu, Zhaohui

2007-01-01

Background Recent advances in Web and information technologies with the increasing decentralization of organizational structures have resulted in massive amounts of information resources and domain-specific services in Traditional Chinese Medicine. The massive volume and diversity of information and services available have made it difficult to achieve seamless and interoperable e-Science for knowledge-intensive disciplines like TCM. Therefore, information integration and service coordination are two major challenges in e-Science for TCM. We still lack sophisticated approaches to integrate scientific data and services for TCM e-Science. Results We present a comprehensive approach to build dynamic and extendable e-Science applications for knowledge-intensive disciplines like TCM based on semantic and knowledge-based techniques. The semantic e-Science infrastructure for TCM supports large-scale database integration and service coordination in a virtual organization. We use domain ontologies to integrate TCM database resources and services in a semantic cyberspace and deliver a semantically superior experience including browsing, searching, querying and knowledge discovering to users. We have developed a collection of semantic-based toolkits to facilitate TCM scientists and researchers in information sharing and collaborative research. Conclusion Semantic and knowledge-based techniques are suitable to knowledge-intensive disciplines like TCM. It's possible to build on-demand e-Science system for TCM based on existing semantic and knowledge-based techniques. The presented approach in the paper integrates heterogeneous distributed TCM databases and services, and provides scientists with semantically superior experience to support collaborative research in TCM discipline. PMID:17493289

Semantic integration of information about orthologs and diseases: the OGO system.

PubMed

Miñarro-Gimenez, Jose Antonio; Egaña Aranguren, Mikel; Martínez Béjar, Rodrigo; Fernández-Breis, Jesualdo Tomás; Madrid, Marisa

2011-12-01

Semantic Web technologies like RDF and OWL are currently applied in life sciences to improve knowledge management by integrating disparate information. Many of the systems that perform such task, however, only offer a SPARQL query interface, which is difficult to use for life scientists. We present the OGO system, which consists of a knowledge base that integrates information of orthologous sequences and genetic diseases, providing an easy to use ontology-constrain driven query interface. Such interface allows the users to define SPARQL queries through a graphical process, therefore not requiring SPARQL expertise. Copyright © 2011 Elsevier Inc. All rights reserved.

Exploring information from the topology beneath the Gene Ontology terms to improve semantic similarity measures.

PubMed

Zhang, Shu-Bo; Lai, Jian-Huang

2016-07-15

Measuring the similarity between pairs of biological entities is important in molecular biology. The introduction of Gene Ontology (GO) provides us with a promising approach to quantifying the semantic similarity between two genes or gene products. This kind of similarity measure is closely associated with the GO terms annotated to biological entities under consideration and the structure of the GO graph. However, previous works in this field mainly focused on the upper part of the graph, and seldom concerned about the lower part. In this study, we aim to explore information from the lower part of the GO graph for better semantic similarity. We proposed a framework to quantify the similarity measure beneath a term pair, which takes into account both the information two ancestral terms share and the probability that they co-occur with their common descendants. The effectiveness of our approach was evaluated against seven typical measurements on public platform CESSM, protein-protein interaction and gene expression datasets. Experimental results consistently show that the similarity derived from the lower part contributes to better semantic similarity measure. The promising features of our approach are the following: (1) it provides a mirror model to characterize the information two ancestral terms share with respect to their common descendant; (2) it quantifies the probability that two terms co-occur with their common descendant in an efficient way; and (3) our framework can effectively capture the similarity measure beneath two terms, which can serve as an add-on to improve traditional semantic similarity measure between two GO terms. The algorithm was implemented in Matlab and is freely available from http://ejl.org.cn/bio/GOBeneath/. Copyright © 2016 Elsevier B.V. All rights reserved.

Revealing common disease mechanisms shared by tumors of different tissues of origin through semantic representation of genomic alterations and topic modeling.

PubMed

Chen, Vicky; Paisley, John; Lu, Xinghua

2017-03-14

Cancer is a complex disease driven by somatic genomic alterations (SGAs) that perturb signaling pathways and consequently cellular function. Identifying patterns of pathway perturbations would provide insights into common disease mechanisms shared among tumors, which is important for guiding treatment and predicting outcome. However, identifying perturbed pathways is challenging, because different tumors can have the same perturbed pathways that are perturbed by different SGAs. Here, we designed novel semantic representations that capture the functional similarity of distinct SGAs perturbing a common pathway in different tumors. Combining this representation with topic modeling would allow us to identify patterns in altered signaling pathways. We represented each gene with a vector of words describing its function, and we represented the SGAs of a tumor as a text document by pooling the words representing individual SGAs. We applied the nested hierarchical Dirichlet process (nHDP) model to a collection of tumors of 5 cancer types from TCGA. We identified topics (consisting of co-occurring words) representing the common functional themes of different SGAs. Tumors were clustered based on their topic associations, such that each cluster consists of tumors sharing common functional themes. The resulting clusters contained mixtures of cancer types, which indicates that different cancer types can share disease mechanisms. Survival analysis based on the clusters revealed significant differences in survival among the tumors of the same cancer type that were assigned to different clusters. The results indicate that applying topic modeling to semantic representations of tumors identifies patterns in the combinations of altered functional pathways in cancer.

Exploiting Recurring Structure in a Semantic Network

NASA Technical Reports Server (NTRS)

Wolfe, Shawn R.; Keller, Richard M.

2004-01-01

With the growing popularity of the Semantic Web, an increasing amount of information is becoming available in machine interpretable, semantically structured networks. Within these semantic networks are recurring structures that could be mined by existing or novel knowledge discovery methods. The mining of these semantic structures represents an interesting area that focuses on mining both for and from the Semantic Web, with surprising applicability to problems confronting the developers of Semantic Web applications. In this paper, we present representative examples of recurring structures and show how these structures could be used to increase the utility of a semantic repository deployed at NASA.

The Semantic Distance Task: Quantifying Semantic Distance with Semantic Network Path Length

ERIC Educational Resources Information Center

Kenett, Yoed N.; Levi, Effi; Anaki, David; Faust, Miriam

2017-01-01

Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We…

A Semantic Approach for Geospatial Information Extraction from Unstructured Documents

NASA Astrophysics Data System (ADS)

Sallaberry, Christian; Gaio, Mauro; Lesbegueries, Julien; Loustau, Pierre

Local cultural heritage document collections are characterized by their content, which is strongly attached to a territory and its land history (i.e., geographical references). Our contribution aims at making the content retrieval process more efficient whenever a query includes geographic criteria. We propose a core model for a formal representation of geographic information. It takes into account characteristics of different modes of expression, such as written language, captures of drawings, maps, photographs, etc. We have developed a prototype that fully implements geographic information extraction (IE) and geographic information retrieval (IR) processes. All PIV prototype processing resources are designed as Web Services. We propose a geographic IE process based on semantic treatment as a supplement to classical IE approaches. We implement geographic IR by using intersection computing algorithms that seek out any intersection between formal geocoded representations of geographic information in a user query and similar representations in document collection indexes.

NASA and The Semantic Web

NASA Technical Reports Server (NTRS)

Ashish, Naveen

2005-01-01

We provide an overview of several ongoing NASA endeavors based on concepts, systems, and technology from the Semantic Web arena. Indeed NASA has been one of the early adopters of Semantic Web Technology and we describe ongoing and completed R&D efforts for several applications ranging from collaborative systems to airspace information management to enterprise search to scientific information gathering and discovery systems at NASA.

Social Networking on the Semantic Web

ERIC Educational Resources Information Center

Finin, Tim; Ding, Li; Zhou, Lina; Joshi, Anupam

2005-01-01

Purpose: Aims to investigate the way that the semantic web is being used to represent and process social network information. Design/methodology/approach: The Swoogle semantic web search engine was used to construct several large data sets of Resource Description Framework (RDF) documents with social network information that were encoded using the…

Processing of visual semantic information to concrete words: temporal dynamics and neural mechanisms indicated by event-related brain potentials( ).

PubMed

van Schie, Hein T; Wijers, Albertus A; Mars, Rogier B; Benjamins, Jeroen S; Stowe, Laurie A

2005-05-01

Event-related brain potentials were used to study the retrieval of visual semantic information to concrete words, and to investigate possible structural overlap between visual object working memory and concreteness effects in word processing. Subjects performed an object working memory task that involved 5 s retention of simple 4-angled polygons (load 1), complex 10-angled polygons (load 2), and a no-load baseline condition. During the polygon retention interval subjects were presented with a lexical decision task to auditory presented concrete (imageable) and abstract (nonimageable) words, and pseudowords. ERP results are consistent with the use of object working memory for the visualisation of concrete words. Our data indicate a two-step processing model of visual semantics in which visual descriptive information of concrete words is first encoded in semantic memory (indicated by an anterior N400 and posterior occipital positivity), and is subsequently visualised via the network for object working memory (reflected by a left frontal positive slow wave and a bilateral occipital slow wave negativity). Results are discussed in the light of contemporary models of semantic memory.

Ontology Reuse in Geoscience Semantic Applications

NASA Astrophysics Data System (ADS)

Mayernik, M. S.; Gross, M. B.; Daniels, M. D.; Rowan, L. R.; Stott, D.; Maull, K. E.; Khan, H.; Corson-Rikert, J.

2015-12-01

The tension between local ontology development and wider ontology connections is fundamental to the Semantic web. It is often unclear, however, what the key decision points should be for new semantic web applications in deciding when to reuse existing ontologies and when to develop original ontologies. In addition, with the growth of semantic web ontologies and applications, new semantic web applications can struggle to efficiently and effectively identify and select ontologies to reuse. This presentation will describe the ontology comparison, selection, and consolidation effort within the EarthCollab project. UCAR, Cornell University, and UNAVCO are collaborating on the EarthCollab project to use semantic web technologies to enable the discovery of the research output from a diverse array of projects. The EarthCollab project is using the VIVO Semantic web software suite to increase discoverability of research information and data related to the following two geoscience-based communities: (1) the Bering Sea Project, an interdisciplinary field program whose data archive is hosted by NCAR's Earth Observing Laboratory (EOL), and (2) diverse research projects informed by geodesy through the UNAVCO geodetic facility and consortium. This presentation will outline of EarthCollab use cases, and provide an overview of key ontologies being used, including the VIVO-Integrated Semantic Framework (VIVO-ISF), Global Change Information System (GCIS), and Data Catalog (DCAT) ontologies. We will discuss issues related to bringing these ontologies together to provide a robust ontological structure to support the EarthCollab use cases. It is rare that a single pre-existing ontology meets all of a new application's needs. New projects need to stitch ontologies together in ways that fit into the broader semantic web ecosystem.

Lexical and sublexical semantic preview benefits in Chinese reading.

PubMed

Yan, Ming; Zhou, Wei; Shu, Hua; Kliegl, Reinhold

2012-07-01

Semantic processing from parafoveal words is an elusive phenomenon in alphabetic languages, but it has been demonstrated only for a restricted set of noncompound Chinese characters. Using the gaze-contingent boundary paradigm, this experiment examined whether parafoveal lexical and sublexical semantic information was extracted from compound preview characters. Results generalized parafoveal semantic processing to this representative set of Chinese characters and extended the parafoveal processing to radical (sublexical) level semantic information extraction. Implications for notions of parafoveal information extraction during Chinese reading are discussed. 2012 APA, all rights reserved

A Left Cerebral Hemisphere's Superiority in Processing Spatial-Categorical Information in a Non-Verbal Semantic Format

ERIC Educational Resources Information Center

Suegami, Takashi; Laeng, Bruno

2013-01-01

It has been shown that the left and right cerebral hemispheres (LH and RH) respectively process qualitative or "categorical" spatial relations and metric or "coordinate" spatial relations. However, categorical spatial information could be thought as divided into two types: semantically-coded and visuospatially-coded categorical information. We…

An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence.

PubMed

Sahoo, Satya S; Bodenreider, Olivier; Rutter, Joni L; Skinner, Karen J; Sheth, Amit P

2008-10-01

This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. RESOURCE PAGE: http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/

Semantic SenseLab: implementing the vision of the Semantic Web in neuroscience

PubMed Central

Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

2011-01-01

Summary Objective Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Methods Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. Conclusion We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/ PMID:20006477

Semantic SenseLab: Implementing the vision of the Semantic Web in neuroscience.

PubMed

Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

2010-01-01

Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/. 2009 Elsevier B.V. All rights reserved.

The Role of Simple Semantics in the Process of Artificial Grammar Learning.

PubMed

Öttl, Birgit; Jäger, Gerhard; Kaup, Barbara

2017-10-01

This study investigated the effect of semantic information on artificial grammar learning (AGL). Recursive grammars of different complexity levels (regular language, mirror language, copy language) were investigated in a series of AGL experiments. In the with-semantics condition, participants acquired semantic information prior to the AGL experiment; in the without-semantics control condition, participants did not receive semantic information. It was hypothesized that semantics would generally facilitate grammar acquisition and that the learning benefit in the with-semantics conditions would increase with increasing grammar complexity. Experiment 1 showed learning effects for all grammars but no performance difference between conditions. Experiment 2 replicated the absence of a semantic benefit for all grammars even though semantic information was more prominent during grammar acquisition as compared to Experiment 1. Thus, we did not find evidence for the idea that semantics facilitates grammar acquisition, which seems to support the view of an independent syntactic processing component.

The effects of shared information on semantic calculations in the gene ontology.

PubMed

Bible, Paul W; Sun, Hong-Wei; Morasso, Maria I; Loganantharaj, Rasiah; Wei, Lai

2017-01-01

The structured vocabulary that describes gene function, the gene ontology (GO), serves as a powerful tool in biological research. One application of GO in computational biology calculates semantic similarity between two concepts to make inferences about the functional similarity of genes. A class of term similarity algorithms explicitly calculates the shared information (SI) between concepts then substitutes this calculation into traditional term similarity measures such as Resnik, Lin, and Jiang-Conrath. Alternative SI approaches, when combined with ontology choice and term similarity type, lead to many gene-to-gene similarity measures. No thorough investigation has been made into the behavior, complexity, and performance of semantic methods derived from distinct SI approaches. We apply bootstrapping to compare the generalized performance of 57 gene-to-gene semantic measures across six benchmarks. Considering the number of measures, we additionally evaluate whether these methods can be leveraged through ensemble machine learning to improve prediction performance. Results showed that the choice of ontology type most strongly influenced performance across all evaluations. Combining measures into an ensemble classifier reduces cross-validation error beyond any individual measure for protein interaction prediction. This improvement resulted from information gained through the combination of ontology types as ensemble methods within each GO type offered no improvement. These results demonstrate that multiple SI measures can be leveraged for machine learning tasks such as automated gene function prediction by incorporating methods from across the ontologies. To facilitate future research in this area, we developed the GO Graph Tool Kit (GGTK), an open source C++ library with Python interface (github.com/paulbible/ggtk).

Intelligent Information Fusion in the Aviation Domain: A Semantic-Web based Approach

NASA Technical Reports Server (NTRS)

Ashish, Naveen; Goforth, Andre

2005-01-01

Information fusion from multiple sources is a critical requirement for System Wide Information Management in the National Airspace (NAS). NASA and the FAA envision creating an "integrated pool" of information originally coming from different sources, which users, intelligent agents and NAS decision support tools can tap into. In this paper we present the results of our initial investigations into the requirements and prototype development of such an integrated information pool for the NAS. We have attempted to ascertain key requirements for such an integrated pool based on a survey of DSS tools that will benefit from this integrated pool. We then advocate key technologies from computer science research areas such as the semantic web, information integration, and intelligent agents that we believe are well suited to achieving the envisioned system wide information management capabilities.

Multi-talker background and semantic priming effect

PubMed Central

Dekerle, Marie; Boulenger, Véronique; Hoen, Michel; Meunier, Fanny

2014-01-01

The reported studies have aimed to investigate whether informational masking in a multi-talker background relies on semantic interference between the background and target using an adapted semantic priming paradigm. In 3 experiments, participants were required to perform a lexical decision task on a target item embedded in backgrounds composed of 1–4 voices. These voices were Semantically Consistent (SC) voices (i.e., pronouncing words sharing semantic features with the target) or Semantically Inconsistent (SI) voices (i.e., pronouncing words semantically unrelated to each other and to the target). In the first experiment, backgrounds consisted of 1 or 2 SC voices. One and 2 SI voices were added in Experiments 2 and 3, respectively. The results showed a semantic priming effect only in the conditions where the number of SC voices was greater than the number of SI voices, suggesting that semantic priming depended on prime intelligibility and strategic processes. However, even if backgrounds were composed of 3 or 4 voices, reducing intelligibility, participants were able to recognize words from these backgrounds, although no semantic priming effect on the targets was observed. Overall this finding suggests that informational masking can occur at a semantic level if intelligibility is sufficient. Based on the Effortfulness Hypothesis, we also suggest that when there is an increased difficulty in extracting target signals (caused by a relatively high number of voices in the background), more cognitive resources were allocated to formal processes (i.e., acoustic and phonological), leading to a decrease in available resources for deeper semantic processing of background words, therefore preventing semantic priming from occurring. PMID:25400572

Explaining Semantic Short-Term Memory Deficits: Evidence for the Critical Role of Semantic Control

ERIC Educational Resources Information Center

Hoffman, Paul; Jefferies, Elizabeth; Lambon Ralph, Matthew A.

2011-01-01

Patients with apparently selective short-term memory (STM) deficits for semantic information have played an important role in developing multi-store theories of STM and challenge the idea that verbal STM is supported by maintaining activation in the language system. We propose that semantic STM deficits are not as selective as previously thought…

The anterior-ventrolateral temporal lobe contributes to boosting visual working memory capacity for items carrying semantic information.

PubMed

Chiou, Rocco; Lambon Ralph, Matthew A

2018-04-01

Working memory (WM) is a buffer that temporarily maintains information, be it visual or auditory, in an active state, caching its contents for online rehearsal or manipulation. How the brain enables long-term semantic knowledge to affect the WM buffer is a theoretically significant issue awaiting further investigation. In the present study, we capitalise on the knowledge about famous individuals as a 'test-case' to study how it impinges upon WM capacity for human faces and its neural substrate. Using continuous theta-burst transcranial stimulation combined with a psychophysical task probing WM storage for varying contents, we provide compelling evidence that (1) faces (regardless of familiarity) continued to accrue in the WM buffer with longer encoding time, whereas for meaningless stimuli (colour shades) there was little increment; (2) the rate of WM accrual was significantly more efficient for famous faces, compared to unknown faces; (3) the right anterior-ventrolateral temporal lobe (ATL) causally mediated this superior WM storage for famous faces. Specifically, disrupting the ATL (a region tuned to semantic knowledge including person identity) selectively hinders WM accrual for celebrity faces while leaving the accrual for unfamiliar faces intact. Further, this 'semantically-accelerated' storage is impervious to disruption of the right middle frontal gyrus and vertex, supporting the specific and causative contribution of the right ATL. Our finding advances the understanding of the neural architecture of WM, demonstrating that it depends on interaction with long-term semantic knowledge underpinned by the ATL, which causally expands the WM buffer when visual content carries semantic information. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Contextually guided very-high-resolution imagery classification with semantic segments

NASA Astrophysics Data System (ADS)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

Unconscious semantic activation depends on feature-specific attention allocation.

PubMed

Spruyt, Adriaan; De Houwer, Jan; Everaert, Tom; Hermans, Dirk

2012-01-01

We examined whether semantic activation by subliminally presented stimuli is dependent upon the extent to which participants assign attention to specific semantic stimulus features and stimulus dimensions. Participants pronounced visible target words that were preceded by briefly presented, masked prime words. Both affective and non-affective semantic congruence of the prime-target pairs were manipulated under conditions that either promoted selective attention for affective stimulus information or selective attention for non-affective semantic stimulus information. In line with our predictions, results showed that affective congruence had a clear impact on word pronunciation latencies only if participants were encouraged to assign attention to the affective stimulus dimension. In contrast, non-affective semantic relatedness of the prime-target pairs produced no priming at all. Our findings are consistent with the hypothesis that unconscious activation of (affective) semantic information is modulated by feature-specific attention allocation. Copyright © 2011 Elsevier B.V. All rights reserved.

HTML5 microdata as a semantic container for medical information exchange.

PubMed

Kimura, Eizen; Kobayashi, Shinji; Ishihara, Ken

2014-01-01

Achieving interoperability between clinical electronic medical records (EMR) systems and cloud computing systems is challenging because of the lack of a universal reference method as a standard for information exchange with a secure connection. Here we describe an information exchange scheme using HTML5 microdata, where the standard semantic container is an HTML document. We embed HL7 messages describing laboratory test results in the microdata. We also annotate items in the clinical research report with the microdata. We mapped the laboratory test result data into the clinical research report using an HL7 selector specified in the microdata. This scheme can provide secure cooperation between the cloud-based service and the EMR system.

An ontology-driven semantic mash-up of gene and biological pathway information: Application to the domain of nicotine dependence

PubMed Central

Sahoo, Satya S.; Bodenreider, Olivier; Rutter, Joni L.; Skinner, Karen J.; Sheth, Amit P.

2008-01-01

Objectives This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. Methods We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Results Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Conclusion Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. Resource page http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/ PMID:18395495

Semantic-Web Technology: Applications at NASA

NASA Technical Reports Server (NTRS)

Ashish, Naveen

2004-01-01

We provide a description of work at the National Aeronautics and Space Administration (NASA) on building system based on semantic-web concepts and technologies. NASA has been one of the early adopters of semantic-web technologies for practical applications. Indeed there are several ongoing 0 endeavors on building semantics based systems for use in diverse NASA domains ranging from collaborative scientific activity to accident and mishap investigation to enterprise search to scientific information gathering and integration to aviation safety decision support We provide a brief overview of many applications and ongoing work with the goal of informing the external community of these NASA endeavors.

SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data

USGS Publications Warehouse

Patton, Evan W.; Seyed, Patrice; Wang, Ping; Fu, Linyun; Dein, F. Joshua; Bristol, R. Sky; McGuinness, Deborah L.

2014-01-01

We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of linked open data. In previous work, we designed and implemented a semantically enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.

Talk this way: the effect of prosodically conveyed semantic information on memory for novel words.

PubMed

Shintel, Hadas; Anderson, Nathan L; Fenn, Kimberly M

2014-08-01

Speakers modulate their prosody to express not only emotional information but also semantic information (e.g., raising pitch for upward motion). Moreover, this information can help listeners infer meaning. Work investigating the communicative role of prosodically conveyed meaning has focused on reference resolution, and potential mnemonic benefits remain unexplored. We investigated the effect of prosody on memory for the meaning of novel words, even when it conveys superfluous information. Participants heard novel words, produced with congruent or incongruent prosody, and viewed image pairs representing the intended meaning and its antonym (e.g., a small and a large dog). Importantly, an arrow indicated the image representing the intended meaning, resolving the ambiguity. Participants then completed 2 memory tests, either immediately after learning or after a 24-hr delay, on which they chose an image (out of a new image pair) and a definition that best represented the word. On the image test, memory was similar on the immediate test, but incongruent prosody led to greater loss over time. On the definition test, memory was better for congruent prosody at both times. Results suggest that listeners extract semantic information from prosody even when it is redundant and that prosody can enhance memory, beyond its role in comprehension. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Exploring the presentation of HPV information online: A semantic network analysis of websites.

PubMed

Ruiz, Jeanette B; Barnett, George A

2015-06-26

Negative vaccination-related information online leads some to opt out of recommended vaccinations. To determine how HPV vaccine information is presented online and what concepts co-occur. A semantic network analysis of the words in first-page Google search results was conducted using three negative, three neutral, and three positive search terms for 10 base concepts such as HPV vaccine, and HPV immunizations. In total, 223 of the 300 websites retrieved met inclusion requirements. Website information was analyzed using network statistics to determine what words most frequently appear, which words co-occur, and the sentiment of the words. High levels of word interconnectivity were found suggesting a rich set of semantic links and a very integrated set of concepts. Limited number of words held centrality indicating limited concept prominence. This dense network signifies concepts that are well connected. Negative words were most prevalent and were associated with describing the HPV vaccine's side-effects as well as the negative effects of HPV and cervical cancer. A smaller cluster focuses on reporting negative vaccine side-effects. Clustering shows the words women and girls closely located to the words sexually, virus, and infection. Information about the HPV vaccine online centered on a limited number of concepts. HPV vaccine benefits as well as the risks of HPV, including severity and susceptibility, were centrally presented. Word cluster results imply that HPV vaccine information for women and girls is discussed in more sexual terms than for men and boys. Copyright © 2015 Elsevier Ltd. All rights reserved.

Selective Short-Term Memory Deficits Arise from Impaired Domain-General Semantic Control Mechanisms

ERIC Educational Resources Information Center

Hoffman, Paul; Jefferies, Elizabeth; Ehsan, Sheeba; Hopper, Samantha; Lambon Ralph, Matthew A.

2009-01-01

Semantic short-term memory (STM) patients have a reduced ability to retain semantic information over brief delays but perform well on other semantic tasks; this pattern suggests damage to a dedicated buffer for semantic information. Alternatively, these difficulties may arise from mild disruption to domain-general semantic processes that have…

Remote semantic memory is impoverished in hippocampal amnesia

PubMed Central

Klooster, Nathaniel B.; Duff, Melissa C.

2015-01-01

The necessity of the hippocampus for acquiring new semantic concepts is a topic of considerable debate. However, it is generally accepted that any role the hippocampus plays in semantic memory is time limited and that previously acquired information becomes independent of the hippocampus over time. This view, along with intact naming and word-definition matching performance in amnesia, has led to the notion that remote semantic memory is intact in patients with hippocampal amnesia. Motivated by perspectives of word learning as a protracted process where additional features and senses of a word are added over time, and by recent discoveries about the time course of hippocampal contributions to on-line relational processing, reconsolidation, and the flexible integration of information, we revisit the notion that remote semantic memory is intact in amnesia. Using measures of semantic richness and vocabulary depth from psycholinguistics and first and second language-learning studies, we examined how much information is associated with previously acquired, highly familiar words in a group of patients with bilateral hippocampal damage and amnesia. Relative to healthy demographically matched comparison participants and a group of brain-damaged comparison participants, the patients with hippocampal amnesia performed significantly worse on both productive and receptive measures of vocabulary depth and semantic richness. These findings suggest that remote semantic memory is impoverished in patients with hippocampal amnesia and that the hippocampus may play a role in the maintenance and updating of semantic memory beyond its initial acquisition. PMID:26474741

Semantic similarity measurement between gene ontology terms based on exclusively inherited shared information.

PubMed

Zhang, Shu-Bo; Lai, Jian-Huang

2015-03-01

Quantifying the semantic similarities between pairs of terms in the Gene Ontology (GO) structure can help to explore the functional relationships between biological entities. A common approach to this problem is to measure the information they have in common based on the information content of their common ancestors. However, many studies have their limitations in measuring the information two GO terms share. This study presented a new measurement, exclusively inherited shared information (EISI) that captured the information shared by two terms based on an intuitive observation on the multiple inheritance relationships among the terms in the GO graph. EISI was derived from the information content of the exclusively inherited common ancestors (EICAs), which were screened from the common ancestors according to the attribute of their direct children. The effectiveness of EISI was evaluated against some state-of-the-art measurements on both artificial and real datasets, it produced more relevant results with experts' scores on the artificial dataset, and supported the prior knowledge of gene function in pathways on the Saccharomyces genome database (SGD). The promising features of EISI are the following: (1) it provides a more effective way to characterize the semantic relationship between two GO terms by taking into account multiple common ancestors related, and (2) can quickly detect all EICAs with time complexity of O(n), which is much more efficient than other methods based on disjunctive common ancestors. It is a promising alternative to multiple inheritance based methods for practical applications on large-scale dataset. The algorithm EISI was implemented in Matlab and is freely available from http://treaton.evai.pl/EISI/. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of semantic similarity between proteins using information content and topological properties of the Gene Ontology graph.

PubMed

Dutta, Pritha; Basu, Subhadip; Kundu, Mahantapas

2017-03-31

The semantic similarity between two interacting proteins can be estimated by combining the similarity scores of the GO terms associated with the proteins. Greater number of similar GO annotations between two proteins indicates greater interaction affinity. Existing semantic similarity measures make use of the GO graph structure, the information content of GO terms, or a combination of both. In this paper, we present a hybrid approach which utilizes both the topological features of the GO graph and information contents of the GO terms. More specifically, we 1) consider a fuzzy clustering of the GO graph based on the level of association of the GO terms, 2) estimate the GO term memberships to each cluster center based on the respective shortest path lengths, and 3) assign weightage to GO term pairs on the basis of their dissimilarity with respect to the cluster centers. We test the performance of our semantic similarity measure against seven other previously published similarity measures using benchmark protein-protein interaction datasets of Homo sapiens and Saccharomyces cerevisiae based on sequence similarity, Pfam similarity, area under ROC curve and F1 measure.

Application of Semantic Tagging to Generate Superimposed Information on a Digital Encyclopedia

NASA Astrophysics Data System (ADS)

Garrido, Piedad; Tramullas, Jesus; Martinez, Francisco J.

We can find in the literature several works regarding the automatic or semi-automatic processing of textual documents with historic information using free software technologies. However, more research work is needed to integrate the analysis of the context and provide coverage to the peculiarities of the Spanish language from a semantic point of view. This research work proposes a novel knowledge-based strategy based on combining subject-centric computing, a topic-oriented approach, and superimposed information. It subsequent combination with artificial intelligence techniques led to an automatic analysis after implementing a made-to-measure interpreted algorithm which, in turn, produced a good number of associations and events with 90% reliability.

Centrality-based Selection of Semantic Resources for Geosciences

NASA Astrophysics Data System (ADS)

Cerba, Otakar; Jedlicka, Karel

2017-04-01

Semantical questions intervene almost in all disciplines dealing with geographic data and information, because relevant semantics is crucial for any way of communication and interaction among humans as well as among machines. But the existence of such a large number of different semantic resources (such as various thesauri, controlled vocabularies, knowledge bases or ontologies) makes the process of semantics implementation much more difficult and complicates the use of the advantages of semantics. This is because in many cases users are not able to find the most suitable resource for their purposes. The research presented in this paper introduces a methodology consisting of an analysis of identical relations in Linked Data space, which covers a majority of semantic resources, to find a suitable resource of semantic information. Identical links interconnect representations of an object or a concept in various semantic resources. Therefore this type of relations is considered to be crucial from the view of Linked Data, because these links provide new additional information, including various views on one concept based on different cultural or regional aspects (so-called social role of Linked Data). For these reasons it is possible to declare that one reasonable criterion for feasible semantic resources for almost all domains, including geosciences, is their position in a network of interconnected semantic resources and level of linking to other knowledge bases and similar products. The presented methodology is based on searching of mutual connections between various instances of one concept using "follow your nose" approach. The extracted data on interconnections between semantic resources are arranged to directed graphs and processed by various metrics patterned on centrality computing (degree, closeness or betweenness centrality). Semantic resources recommended by the research could be used for providing semantically described keywords for metadata records or as

Latent Semantic Analysis.

ERIC Educational Resources Information Center

Dumais, Susan T.

2004-01-01

Presents a literature review that covers the following topics related to Latent Semantic Analysis (LSA): (1) LSA overview; (2) applications of LSA, including information retrieval (IR), information filtering, cross-language retrieval, and other IR-related LSA applications; (3) modeling human memory, including the relationship of LSA to other…

Semantic web data warehousing for caGrid.

PubMed

McCusker, James P; Phillips, Joshua A; González Beltrán, Alejandra; Finkelstein, Anthony; Krauthammer, Michael

2009-10-01

The National Cancer Institute (NCI) is developing caGrid as a means for sharing cancer-related data and services. As more data sets become available on caGrid, we need effective ways of accessing and integrating this information. Although the data models exposed on caGrid are semantically well annotated, it is currently up to the caGrid client to infer relationships between the different models and their classes. In this paper, we present a Semantic Web-based data warehouse (Corvus) for creating relationships among caGrid models. This is accomplished through the transformation of semantically-annotated caBIG Unified Modeling Language (UML) information models into Web Ontology Language (OWL) ontologies that preserve those semantics. We demonstrate the validity of the approach by Semantic Extraction, Transformation and Loading (SETL) of data from two caGrid data sources, caTissue and caArray, as well as alignment and query of those sources in Corvus. We argue that semantic integration is necessary for integration of data from distributed web services and that Corvus is a useful way of accomplishing this. Our approach is generalizable and of broad utility to researchers facing similar integration challenges.

Semantic web data warehousing for caGrid

PubMed Central

McCusker, James P; Phillips, Joshua A; Beltrán, Alejandra González; Finkelstein, Anthony; Krauthammer, Michael

2009-01-01

The National Cancer Institute (NCI) is developing caGrid as a means for sharing cancer-related data and services. As more data sets become available on caGrid, we need effective ways of accessing and integrating this information. Although the data models exposed on caGrid are semantically well annotated, it is currently up to the caGrid client to infer relationships between the different models and their classes. In this paper, we present a Semantic Web-based data warehouse (Corvus) for creating relationships among caGrid models. This is accomplished through the transformation of semantically-annotated caBIG® Unified Modeling Language (UML) information models into Web Ontology Language (OWL) ontologies that preserve those semantics. We demonstrate the validity of the approach by Semantic Extraction, Transformation and Loading (SETL) of data from two caGrid data sources, caTissue and caArray, as well as alignment and query of those sources in Corvus. We argue that semantic integration is necessary for integration of data from distributed web services and that Corvus is a useful way of accomplishing this. Our approach is generalizable and of broad utility to researchers facing similar integration challenges. PMID:19796399

XSemantic: An Extension of LCA Based XML Semantic Search

NASA Astrophysics Data System (ADS)

Supasitthimethee, Umaporn; Shimizu, Toshiyuki; Yoshikawa, Masatoshi; Porkaew, Kriengkrai

One of the most convenient ways to query XML data is a keyword search because it does not require any knowledge of XML structure or learning a new user interface. However, the keyword search is ambiguous. The users may use different terms to search for the same information. Furthermore, it is difficult for a system to decide which node is likely to be chosen as a return node and how much information should be included in the result. To address these challenges, we propose an XML semantic search based on keywords called XSemantic. On the one hand, we give three definitions to complete in terms of semantics. Firstly, the semantic term expansion, our system is robust from the ambiguous keywords by using the domain ontology. Secondly, to return semantic meaningful answers, we automatically infer the return information from the user queries and take advantage of the shortest path to return meaningful connections between keywords. Thirdly, we present the semantic ranking that reflects the degree of similarity as well as the semantic relationship so that the search results with the higher relevance are presented to the users first. On the other hand, in the LCA and the proximity search approaches, we investigated the problem of information included in the search results. Therefore, we introduce the notion of the Lowest Common Element Ancestor (LCEA) and define our simple rule without any requirement on the schema information such as the DTD or XML Schema. The first experiment indicated that XSemantic not only properly infers the return information but also generates compact meaningful results. Additionally, the benefits of our proposed semantics are demonstrated by the second experiment.

Remote semantic memory is impoverished in hippocampal amnesia.

PubMed

Klooster, Nathaniel B; Duff, Melissa C

2015-12-01

The necessity of the hippocampus for acquiring new semantic concepts is a topic of considerable debate. However, it is generally accepted that any role the hippocampus plays in semantic memory is time limited and that previously acquired information becomes independent of the hippocampus over time. This view, along with intact naming and word-definition matching performance in amnesia, has led to the notion that remote semantic memory is intact in patients with hippocampal amnesia. Motivated by perspectives of word learning as a protracted process where additional features and senses of a word are added over time, and by recent discoveries about the time course of hippocampal contributions to on-line relational processing, reconsolidation, and the flexible integration of information, we revisit the notion that remote semantic memory is intact in amnesia. Using measures of semantic richness and vocabulary depth from psycholinguistics and first and second language-learning studies, we examined how much information is associated with previously acquired, highly familiar words in a group of patients with bilateral hippocampal damage and amnesia. Relative to healthy demographically matched comparison participants and a group of brain-damaged comparison participants, the patients with hippocampal amnesia performed significantly worse on both productive and receptive measures of vocabulary depth and semantic richness. These findings suggest that remote semantic memory is impoverished in patients with hippocampal amnesia and that the hippocampus may play a role in the maintenance and updating of semantic memory beyond its initial acquisition. Copyright © 2015 Elsevier Ltd. All rights reserved.

Categorizing words through semantic memory navigation

NASA Astrophysics Data System (ADS)

Borge-Holthoefer, J.; Arenas, A.

2010-03-01

Semantic memory is the cognitive system devoted to storage and retrieval of conceptual knowledge. Empirical data indicate that semantic memory is organized in a network structure. Everyday experience shows that word search and retrieval processes provide fluent and coherent speech, i.e. are efficient. This implies either that semantic memory encodes, besides thousands of words, different kind of links for different relationships (introducing greater complexity and storage costs), or that the structure evolves facilitating the differentiation between long-lasting semantic relations from incidental, phenomenological ones. Assuming the latter possibility, we explore a mechanism to disentangle the underlying semantic backbone which comprises conceptual structure (extraction of categorical relations between pairs of words), from the rest of information present in the structure. To this end, we first present and characterize an empirical data set modeled as a network, then we simulate a stochastic cognitive navigation on this topology. We schematize this latter process as uncorrelated random walks from node to node, which converge to a feature vectors network. By doing so we both introduce a novel mechanism for information retrieval, and point at the problem of category formation in close connection to linguistic and non-linguistic experience.

Preserved semantic access in global amnesia and hippocampal damage.

PubMed

Giovagnoli, A R; Erbetta, A; Bugiani, O

2001-12-01

C.B., a right-handed 33-year-old man, presented with anterograde amnesia after acute heart block. Cognitive abilities were normal except for serious impairment of long-term episodic memory. The access to semantic information was fully preserved. Magnetic resonance showed high signal intensity and marked volume loss in the hippocampus bilaterally; the left and right parahippocampal gyrus, lateral occipito-temporal gyrus, inferior temporal gyrus, and lateral temporal cortex were normal. This case underlines that global amnesia associated with hippocampal damage does not affect semantic memory. Although the hippocampus is important in retrieving context-linked information, its role is not so crucial in retrieving semantic contents. Cortical areas surrounding the hippocampus and lateral temporal areas might guide the recall of semantic information.

Disruption of Semantic Network in Mild Alzheimer's Disease Revealed by Resting-State fMRI.

PubMed

Mascali, Daniele; DiNuzzo, Mauro; Serra, Laura; Mangia, Silvia; Maraviglia, Bruno; Bozzali, Marco; Giove, Federico

2018-02-10

Subtle semantic deficits can be observed in Alzheimer's disease (AD) patients even in the early stages of the illness. In this work, we tested the hypothesis that the semantic control network is deregulated in mild AD patients. We assessed the integrity of the semantic control system using resting-state functional magnetic resonance imaging in a cohort of patients with mild AD (n = 38; mean mini-mental state examination = 20.5) and in a group of age-matched healthy controls (n = 19). Voxel-wise analysis spatially constrained in the left fronto-temporal semantic control network identified two regions with altered functional connectivity (FC) in AD patients, specifically in the pars opercularis (POp, BA44) and in the posterior middle temporal gyrus (pMTG, BA21). Using whole-brain seed-based analysis, we demonstrated that these two regions have altered FC even beyond the semantic control network. In particular, the pMTG displayed a wide-distributed pattern of lower connectivity to several brain regions involved in language-semantic processing, along with a possibly compensatory higher connectivity to the Wernicke's area. We conclude that in mild AD brain regions belonging to the semantic control network are abnormally connected not only within the network, but also to other areas known to be critical for language processing. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Hippocampal activation during retrieval of spatial context from episodic and semantic memory.

PubMed

Hoscheidt, Siobhan M; Nadel, Lynn; Payne, Jessica; Ryan, Lee

2010-10-15

The hippocampus, a region implicated in the processing of spatial information and episodic memory, is central to the debate concerning the relationship between episodic and semantic memory. Studies of medial temporal lobe amnesic patients provide evidence that the hippocampus is critical for the retrieval of episodic but not semantic memory. On the other hand, recent neuroimaging studies of intact individuals report hippocampal activation during retrieval of both autobiographical memories and semantic information that includes historical facts, famous faces, and categorical information, suggesting that episodic and semantic memory may engage the hippocampus during memory retrieval in similar ways. Few studies have matched episodic and semantic tasks for the degree to which they include spatial content, even though spatial content may be what drives hippocampal activation during semantic retrieval. To examine this issue, we conducted a functional magnetic resonance imaging (fMRI) study in which retrieval of spatial and nonspatial information was compared during an episodic and semantic recognition task. Results show that the hippocampus (1) participates preferentially in the retrieval of episodic memories; (2) is also engaged by retrieval of semantic memories, particularly those that include spatial information. These data suggest that sharp dissociations between episodic and semantic memory may be overly simplistic and that the hippocampus plays a role in the retrieval of spatial content whether drawn from a memory of one's own life experiences or real-world semantic knowledge. Published by Elsevier B.V.

Chemical Entity Semantic Specification: Knowledge representation for efficient semantic cheminformatics and facile data integration

PubMed Central

2011-01-01

Background Over the past several centuries, chemistry has permeated virtually every facet of human lifestyle, enriching fields as diverse as medicine, agriculture, manufacturing, warfare, and electronics, among numerous others. Unfortunately, application-specific, incompatible chemical information formats and representation strategies have emerged as a result of such diverse adoption of chemistry. Although a number of efforts have been dedicated to unifying the computational representation of chemical information, disparities between the various chemical databases still persist and stand in the way of cross-domain, interdisciplinary investigations. Through a common syntax and formal semantics, Semantic Web technology offers the ability to accurately represent, integrate, reason about and query across diverse chemical information. Results Here we specify and implement the Chemical Entity Semantic Specification (CHESS) for the representation of polyatomic chemical entities, their substructures, bonds, atoms, and reactions using Semantic Web technologies. CHESS provides means to capture aspects of their corresponding chemical descriptors, connectivity, functional composition, and geometric structure while specifying mechanisms for data provenance. We demonstrate that using our readily extensible specification, it is possible to efficiently integrate multiple disparate chemical data sources, while retaining appropriate correspondence of chemical descriptors, with very little additional effort. We demonstrate the impact of some of our representational decisions on the performance of chemically-aware knowledgebase searching and rudimentary reaction candidate selection. Finally, we provide access to the tools necessary to carry out chemical entity encoding in CHESS, along with a sample knowledgebase. Conclusions By harnessing the power of Semantic Web technologies with CHESS, it is possible to provide a means of facile cross-domain chemical knowledge integration with full

Chemical Entity Semantic Specification: Knowledge representation for efficient semantic cheminformatics and facile data integration.

PubMed

Chepelev, Leonid L; Dumontier, Michel

2011-05-19

Over the past several centuries, chemistry has permeated virtually every facet of human lifestyle, enriching fields as diverse as medicine, agriculture, manufacturing, warfare, and electronics, among numerous others. Unfortunately, application-specific, incompatible chemical information formats and representation strategies have emerged as a result of such diverse adoption of chemistry. Although a number of efforts have been dedicated to unifying the computational representation of chemical information, disparities between the various chemical databases still persist and stand in the way of cross-domain, interdisciplinary investigations. Through a common syntax and formal semantics, Semantic Web technology offers the ability to accurately represent, integrate, reason about and query across diverse chemical information. Here we specify and implement the Chemical Entity Semantic Specification (CHESS) for the representation of polyatomic chemical entities, their substructures, bonds, atoms, and reactions using Semantic Web technologies. CHESS provides means to capture aspects of their corresponding chemical descriptors, connectivity, functional composition, and geometric structure while specifying mechanisms for data provenance. We demonstrate that using our readily extensible specification, it is possible to efficiently integrate multiple disparate chemical data sources, while retaining appropriate correspondence of chemical descriptors, with very little additional effort. We demonstrate the impact of some of our representational decisions on the performance of chemically-aware knowledgebase searching and rudimentary reaction candidate selection. Finally, we provide access to the tools necessary to carry out chemical entity encoding in CHESS, along with a sample knowledgebase. By harnessing the power of Semantic Web technologies with CHESS, it is possible to provide a means of facile cross-domain chemical knowledge integration with full preservation of data

Relations between Short-term Memory Deficits, Semantic Processing, and Executive Function

PubMed Central

Allen, Corinne M.; Martin, Randi C.; Martin, Nadine

2012-01-01

Background Previous research has suggested separable short-term memory (STM) buffers for the maintenance of phonological and lexical-semantic information, as some patients with aphasia show better ability to retain semantic than phonological information and others show the reverse. Recently, researchers have proposed that deficits to the maintenance of semantic information in STM are related to executive control abilities. Aims The present study investigated the relationship of executive function abilities with semantic and phonological short-term memory (STM) and semantic processing in such patients, as some previous research has suggested that semantic STM deficits and semantic processing abilities are critically related to specific or general executive function deficits. Method and Procedures 20 patients with aphasia and STM deficits were tested on measures of short-term retention, semantic processing, and both complex and simple executive function tasks. Outcome and Results In correlational analyses, we found no relation between semantic STM and performance on simple or complex executive function tasks. In contrast, phonological STM was related to executive function performance in tasks that had a verbal component, suggesting that performance in some executive function tasks depends on maintaining or rehearsing phonological codes. Although semantic STM was not related to executive function ability, performance on semantic processing tasks was related to executive function, perhaps due to similar executive task requirements in both semantic processing and executive function tasks. Conclusions Implications for treatment and interpretations of executive deficits are discussed. PMID:22736889

Automatic information extraction from unstructured mammography reports using distributed semantics.

PubMed

Gupta, Anupama; Banerjee, Imon; Rubin, Daniel L

2018-02-01

To date, the methods developed for automated extraction of information from radiology reports are mainly rule-based or dictionary-based, and, therefore, require substantial manual effort to build these systems. Recent efforts to develop automated systems for entity detection have been undertaken, but little work has been done to automatically extract relations and their associated named entities in narrative radiology reports that have comparable accuracy to rule-based methods. Our goal is to extract relations in a unsupervised way from radiology reports without specifying prior domain knowledge. We propose a hybrid approach for information extraction that combines dependency-based parse tree with distributed semantics for generating structured information frames about particular findings/abnormalities from the free-text mammography reports. The proposed IE system obtains a F 1 -score of 0.94 in terms of completeness of the content in the information frames, which outperforms a state-of-the-art rule-based system in this domain by a significant margin. The proposed system can be leveraged in a variety of applications, such as decision support and information retrieval, and may also easily scale to other radiology domains, since there is no need to tune the system with hand-crafted information extraction rules. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Improving User Experience by Taking Advance of Semantic Information of Microformats on Municipal Websites

NASA Astrophysics Data System (ADS)

Rodríguez, Rocío; Vera, Pablo; Estevez, Elsa; Giulianelli, Daniel; Welicki, León; Trigueros, Artemisa

This research regards about the use of microformats as a tool to add semantic information to government web sites. The use of microformats allows the developer to add different resources such as maps, calendars, etc, in an easy way. The paper also shows a survey of the already existing microformats and which of them are useful to be applied to government web sites.

Semantics-informed cartography: the case of Piemonte Geological Map

NASA Astrophysics Data System (ADS)

Piana, Fabrizio; Lombardo, Vincenzo; Mimmo, Dario; Giardino, Marco; Fubelli, Giandomenico

2016-04-01

In modern digital geological maps, namely those supported by a large geo-database and devoted to dynamical, interactive representation on WMS-WebGIS services, there is the need to provide, in an explicit form, the geological assumptions used for the design and compilation of the database of the Map, and to get a definition and/or adoption of semantic representation and taxonomies, in order to achieve a formal and interoperable representation of the geologic knowledge. These approaches are fundamental for the integration and harmonisation of geological information and services across cultural (e.g. different scientific disciplines) and/or physical barriers (e.g. administrative boundaries). Initiatives such as GeoScience Markup Language (last version is GeoSciML 4.0, 2015, http://www.geosciml.org) and the INSPIRE "Data Specification on Geology" http://inspire.jrc.ec.europa.eu/documents/Data_Specifications/INSPIRE_DataSpecification_GE_v3.0rc3.pdf (an operative simplification of GeoSciML, last version is 3.0 rc3, 2013), as well as the recent terminological shepherding of the Geoscience Terminology Working Group (GTWG) have been promoting information exchange of the geologic knowledge. Grounded on these standard vocabularies, schemas and data models, we provide a shared semantic classification of geological data referring to the study case of the synthetic digital geological map of the Piemonte region (NW Italy), named "GEOPiemonteMap", developed by the CNR Institute of Geosciences and Earth Resources, Torino (CNR IGG TO) and hosted as a dynamical interactive map on the geoportal of ARPA Piemonte Environmental Agency. The Piemonte Geological Map is grounded on a regional-scale geo-database consisting of some hundreds of GeologicUnits whose thousands instances (Mapped Features, polygons geometry) widely occur in Piemonte region, and each one is bounded by GeologicStructures (Mapped Features, line geometry). GeologicUnits and GeologicStructures have been spatially

Knowledge of the human body: a distinct semantic domain.

PubMed

Coslett, H Branch; Saffran, Eleanor M; Schwoebel, John

2002-08-13

Patients with selective deficits in the naming and comprehension of animals, plants, and artifacts have been reported. These descriptions of specific semantic category deficits have contributed substantially to the understanding of the architecture of semantic representations. This study sought to further understanding of the organization of the semantic system by demonstrating that another semantic category, knowledge of the human body, may be selectively preserved. The performance of a patient with semantic dementia was compared with the performance of healthy controls on a variety of tasks assessing distinct types of body representations, including the body schema, body image, and body structural description. Despite substantial deficits on tasks involving language and knowledge of the world generally, the patient performed normally on all tests of body knowledge except body part naming; even in this naming task, however, her performance with body parts was significantly better than on artifacts. The demonstration that body knowledge may be preserved despite substantial semantic deficits involving other types of semantic information argues that body knowledge is a distinct and dissociable semantic category. These data are interpreted as support for a model of semantics that proposes that knowledge is distributed across different cortical regions reflecting the manner in which the information was acquired.

From ontology selection and semantic web to an integrated information system for food-borne diseases and food safety.

PubMed

Yan, Xianghe; Peng, Yun; Meng, Jianghong; Ruzante, Juliana; Fratamico, Pina M; Huang, Lihan; Juneja, Vijay; Needleman, David S

2011-01-01

Several factors have hindered effective use of information and resources related to food safety due to inconsistency among semantically heterogeneous data resources, lack of knowledge on profiling of food-borne pathogens, and knowledge gaps among research communities, government risk assessors/managers, and end-users of the information. This paper discusses technical aspects in the establishment of a comprehensive food safety information system consisting of the following steps: (a) computational collection and compiling publicly available information, including published pathogen genomic, proteomic, and metabolomic data; (b) development of ontology libraries on food-borne pathogens and design automatic algorithms with formal inference and fuzzy and probabilistic reasoning to address the consistency and accuracy of distributed information resources (e.g., PulseNet, FoodNet, OutbreakNet, PubMed, NCBI, EMBL, and other online genetic databases and information); (c) integration of collected pathogen profiling data, Foodrisk.org ( http://www.foodrisk.org ), PMP, Combase, and other relevant information into a user-friendly, searchable, "homogeneous" information system available to scientists in academia, the food industry, and government agencies; and (d) development of a computational model in semantic web for greater adaptability and robustness.

Simulating Expert Clinical Comprehension: Adapting Latent Semantic Analysis to Accurately Extract Clinical Concepts from Psychiatric Narrative

PubMed Central

Cohen, Trevor; Blatter, Brett; Patel, Vimla

2008-01-01

Cognitive studies reveal that less-than-expert clinicians are less able to recognize meaningful patterns of data in clinical narratives. Accordingly, psychiatric residents early in training fail to attend to information that is relevant to diagnosis and the assessment of dangerousness. This manuscript presents cognitively motivated methodology for the simulation of expert ability to organize relevant findings supporting intermediate diagnostic hypotheses. Latent Semantic Analysis is used to generate a semantic space from which meaningful associations between psychiatric terms are derived. Diagnostically meaningful clusters are modeled as geometric structures within this space and compared to elements of psychiatric narrative text using semantic distance measures. A learning algorithm is defined that alters components of these geometric structures in response to labeled training data. Extraction and classification of relevant text segments is evaluated against expert annotation, with system-rater agreement approximating rater-rater agreement. A range of biomedical informatics applications for these methods are suggested. PMID:18455483

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention

PubMed Central

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-01

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features. PMID:26759193

How Semantic Radicals in Chinese characters Facilitate Hierarchical Category-Based Induction.

PubMed

Wang, Xiaoxi; Ma, Xie; Tao, Yun; Tao, Yachen; Li, Hong

2018-04-03

Prior studies indicate that the semantic radical in Chinese characters contains category information that can support the independent retrieval of category information through the lexical network to the conceptual network. Inductive reasoning relies on category information; thus, semantic radicals may influence inductive reasoning. As most natural concepts are hierarchically structured in the human brain, this study examined how semantic radicals impact inductive reasoning for hierarchical concepts. The study used animal and plant nouns, organized in basic, superordinate, and subordinate levels; half had a semantic radical and half did not. Eighteen participants completed an inductive reasoning task. Behavioural and event-related potential (ERP) data were collected. The behavioural results showed that participants reacted faster and more accurately in the with-semantic-radical condition than in the without-semantic-radical condition. For the ERPs, differences between the conditions were found, and these differences lasted from the very early cognitive processing stage (i.e., the N1 time window) to the relatively late processing stages (i.e., the N400 and LPC time windows). Semantic radicals can help to distinguish the hierarchies earlier (in the N400 period) than characters without a semantic radical (in the LPC period). These results provide electrophysiological evidence that semantic radicals may improve sensitivity to distinguish between hierarchical concepts.

Methods and apparatus for multi-resolution replication of files in a parallel computing system using semantic information

DOEpatents

Faibish, Sorin; Bent, John M.; Tzelnic, Percy; Grider, Gary; Torres, Aaron

2015-10-20

Techniques are provided for storing files in a parallel computing system using different resolutions. A method is provided for storing at least one file generated by a distributed application in a parallel computing system. The file comprises one or more of a complete file and a sub-file. The method comprises the steps of obtaining semantic information related to the file; generating a plurality of replicas of the file with different resolutions based on the semantic information; and storing the file and the plurality of replicas of the file in one or more storage nodes of the parallel computing system. The different resolutions comprise, for example, a variable number of bits and/or a different sub-set of data elements from the file. A plurality of the sub-files can be merged to reproduce the file.

Language Networks Associated with Computerized Semantic Indices

PubMed Central

Pakhomov, Serguei V. S.; Jones, David T.; Knopman, David S.

2014-01-01

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. PMID:25315785

Language networks associated with computerized semantic indices.

PubMed

Pakhomov, Serguei V S; Jones, David T; Knopman, David S

2015-01-01

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. Copyright © 2014 Elsevier Inc. All rights reserved.

Semantic-based crossmodal processing during visual suppression.

PubMed

Cox, Dustin; Hong, Sang Wook

2015-01-01

To reveal the mechanisms underpinning the influence of auditory input on visual awareness, we examine, (1) whether purely semantic-based multisensory integration facilitates the access to visual awareness for familiar visual events, and (2) whether crossmodal semantic priming is the mechanism responsible for the semantic auditory influence on visual awareness. Using continuous flash suppression, we rendered dynamic and familiar visual events (e.g., a video clip of an approaching train) inaccessible to visual awareness. We manipulated the semantic auditory context of the videos by concurrently pairing them with a semantically matching soundtrack (congruent audiovisual condition), a semantically non-matching soundtrack (incongruent audiovisual condition), or with no soundtrack (neutral video-only condition). We found that participants identified the suppressed visual events significantly faster (an earlier breakup of suppression) in the congruent audiovisual condition compared to the incongruent audiovisual condition and video-only condition. However, this facilitatory influence of semantic auditory input was only observed when audiovisual stimulation co-occurred. Our results suggest that the enhanced visual processing with a semantically congruent auditory input occurs due to audiovisual crossmodal processing rather than semantic priming, which may occur even when visual information is not available to visual awareness.

Interconnected growing self-organizing maps for auditory and semantic acquisition modeling

PubMed Central

Cao, Mengxue; Li, Aijun; Fang, Qiang; Kaufmann, Emily; Kröger, Bernd J.

2014-01-01

Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM) algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic–semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners. A reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1) I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2) clear auditory and semantic boundaries can be found in the network representation; (3) cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4) reinforcing-by-link training leads to well-perceived auditory–semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model. PMID:24688478

Interconnected growing self-organizing maps for auditory and semantic acquisition modeling.

PubMed

Cao, Mengxue; Li, Aijun; Fang, Qiang; Kaufmann, Emily; Kröger, Bernd J

2014-01-01

Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM) algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic-semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners. A reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1) I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2) clear auditory and semantic boundaries can be found in the network representation; (3) cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4) reinforcing-by-link training leads to well-perceived auditory-semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model.

On the Semantics of SPARQL

NASA Astrophysics Data System (ADS)

Arenas, Marcelo; Gutierrez, Claudio; Pérez, Jorge

The Resource Description Framework (RDF) is the standard data model for representing information about World Wide Web resources. In January 2008, it was released the recommendation of the W3C for querying RDF data, a query language called SPARQL. In this chapter, we give a detailed description of the semantics of this language. We start by focusing on the definition of a formal semantics for the core part of SPARQL, and then move to the definition for the entire language, including all the features in the specification of SPARQL by the W3C such as blank nodes in graph patterns and bag semantics for solutions.

An Educational Tool for Browsing the Semantic Web

ERIC Educational Resources Information Center

Yoo, Sujin; Kim, Younghwan; Park, Seongbin

2013-01-01

The Semantic Web is an extension of the current Web where information is represented in a machine processable way. It is not separate from the current Web and one of the confusions that novice users might have is where the Semantic Web is. In fact, users can easily encounter RDF documents that are components of the Semantic Web while they navigate…

A Contextual Information Acquisition Approach Based on Semantics and Mashup Technology

NASA Astrophysics Data System (ADS)

He, Yangfan; Li, Lu; He, Keqing; Chen, Xiuhong

Pay per use is an essential feature of cloud computing. Users can make use of some parts of a large scale service to satisfy their requirements, merely at the cost of a little payment. A good understanding of the users' requirement is a prerequisite for choosing the service in need precisely. Context implies users' potential requirements, which can be a complement to the requirements delivered explicitly. However, traditional context-aware computing research always demands some specific kinds of sensors to acquire contextual information, which renders a threshold too high for an application to become context-aware. This paper comes up with an approach which combines contextual information obtained directly and indirectly from the cloud services. Semantic relationship between different kinds of contexts lays foundation for the searching of the cloud services. And mashup technology is adopted to compose the heterogonous services. Abundant contextual information may lend strong support to a comprehensive understanding of users' context and a bettered abstraction of contextual requirements.

Disruption of Semantic Network in Mild Alzheimer’s Disease Revealed by Resting-State fMRI

PubMed Central

Mascali, Daniele; DiNuzzo, Mauro; Serra, Laura; Mangia, Silvia; Maraviglia, Bruno; Bozzali, Marco; Giove, Federico

2018-01-01

Subtle semantic deficits can be observed in Alzheimer’s disease (AD) patients even in the early stages of the illness. In this work, we tested the hypothesis that the semantic control network is deregulated in mild AD patients. We assessed the integrity of the semantic control system using resting-state functional magnetic resonance imaging in a cohort of patients with mild AD (n = 38; mean mini-mental state examination = 20.5) and in a group of age-matched healthy controls (n = 19). Voxel-wise analysis spatially constrained in the left fronto-temporal semantic control network identified two regions with altered functional connectivity (FC) in AD patients, specifically in the pars opercularis (POp, BA44) and in the posterior middle temporal gyrus (pMTG, BA21). Using whole-brain seed-based analysis, we demonstrated that these two regions have altered FC even beyond the semantic control network. In particular, the pMTG displayed a wide-distributed pattern of lower connectivity to several brain regions involved in language-semantic processing, along with a possibly compensatory higher connectivity to the Wernicke’s area. We conclude that in mild AD brain regions belonging to the semantic control network are abnormally connected not only within the network, but also to other areas known to be critical for language processing. PMID:29197559

The Role of Simple Semantics in the Process of Artificial Grammar Learning

ERIC Educational Resources Information Center

Öttl, Birgit; Jäger, Gerhard; Kaup, Barbara

2017-01-01

This study investigated the effect of semantic information on artificial grammar learning (AGL). Recursive grammars of different complexity levels (regular language, mirror language, copy language) were investigated in a series of AGL experiments. In the with-semantics condition, participants acquired semantic information prior to the AGL…

Insights from child development on the relationship between episodic and semantic memory.

PubMed

Robertson, Erin K; Köhler, Stefan

2007-11-05

The present study was motivated by a recent controversy in the neuropsychological literature on semantic dementia as to whether episodic encoding requires semantic processing or whether it can proceed solely based on perceptual processing. We addressed this issue by examining the effect of age-related limitations in semantic competency on episodic memory in 4-6-year-old children (n=67). We administered three different forced-choice recognition memory tests for pictures previously encountered in a single study episode. The tests varied in the degree to which access to semantically encoded information was required at retrieval. Semantic competency predicted recognition performance regardless of whether access to semantic information was required. A direct relation between picture naming at encoding and subsequent recognition was also found for all tests. Our findings emphasize the importance of semantic encoding processes even in retrieval situations that purportedly do not require access to semantic information. They also highlight the importance of testing neuropsychological models of memory in different populations, healthy and brain damaged, at both ends of the developmental continuum.

The Semantic Web: From Representation to Realization

NASA Astrophysics Data System (ADS)

Thórisson, Kristinn R.; Spivack, Nova; Wissner, James M.

A semantically-linked web of electronic information - the Semantic Web - promises numerous benefits including increased precision in automated information sorting, searching, organizing and summarizing. Realizing this requires significantly more reliable meta-information than is readily available today. It also requires a better way to represent information that supports unified management of diverse data and diverse Manipulation methods: from basic keywords to various types of artificial intelligence, to the highest level of intelligent manipulation - the human mind. How this is best done is far from obvious. Relying solely on hand-crafted annotation and ontologies, or solely on artificial intelligence techniques, seems less likely for success than a combination of the two. In this paper describe an integrated, complete solution to these challenges that has already been implemented and tested with hundreds of thousands of users. It is based on an ontological representational level we call SemCards that combines ontological rigour with flexible user interface constructs. SemCards are machine- and human-readable digital entities that allow non-experts to create and use semantic content, while empowering machines to better assist and participate in the process. SemCards enable users to easily create semantically-grounded data that in turn acts as examples for automation processes, creating a positive iterative feedback loop of metadata creation and refinement between user and machine. They provide a holistic solution to the Semantic Web, supporting powerful management of the full lifecycle of data, including its creation, retrieval, classification, sorting and sharing. We have implemented the SemCard technology on the semantic Web site Twine.com, showing that the technology is indeed versatile and scalable. Here we present the key ideas behind SemCards and describe the initial implementation of the technology.

Enabling task-based information prioritization via semantic web encodings

NASA Astrophysics Data System (ADS)

Michaelis, James R.

2016-05-01

Modern Soldiers rely upon accurate and actionable information technology to achieve mission objectives. While increasingly rich sensor networks for Areas of Operation (AO) can offer many directions for aiding Soldiers, limitations are imposed by current tactical edge systems on the rate that content can be transmitted. Furthermore, mission tasks will often require very specific sets of information which may easily be drowned out by other content sources. Prior research on Quality and Value of Information (QoI/VoI) has aimed to define ways to prioritize information objects based on their intrinsic attributes (QoI) and perceived value to a consumer (VoI). As part of this effort, established ranking approaches for obtaining Subject Matter Expert (SME) recommendations, such as the Analytic Hierarchy Process (AHP) have been considered. However, limited work has been done to tie Soldier context - such as descriptions of their mission and tasks - back to intrinsic attributes of information objects. As a first step toward addressing the above challenges, this work introduces an ontology-backed approach - rooted in Semantic Web publication practices - for expressing both AHP decision hierarchies and corresponding SME feedback. Following a short discussion on related QoI/VoI research, an ontology-based data structure is introduced for supporting evaluation of Information Objects, using AHP rankings designed to facilitate information object prioritization. Consistent with alternate AHP approaches, prioritization in this approach is based on pairwise comparisons between Information Objects with respect to established criteria, as well as on pairwise comparison of the criteria to assess their relative importance. The paper concludes with a discussion of both ongoing and future work.

Semantic Technologies and Bio-Ontologies.

PubMed

Gutierrez, Fernando

2017-01-01

As information available through data repositories constantly grows, the need for automated mechanisms for linking, querying, and sharing data has become a relevant factor both in research and industry. This situation is more evident in research fields such as the life sciences, where new experiments by different research groups are constantly generating new information regarding a wide variety of related study objects. However, current methods for representing information and knowledge are not suited for machine processing. The Semantic Technologies are a set of standards and protocols that intend to provide methods for representing and handling data that encourages reusability of information and is machine-readable. In this chapter, we will provide a brief introduction to Semantic Technologies, and how these protocols and standards have been incorporated into the life sciences to facilitate dissemination and access to information.

A logical approach to semantic interoperability in healthcare.

PubMed

Bird, Linda; Brooks, Colleen; Cheong, Yu Chye; Tun, Nwe Ni

2011-01-01

Singapore is in the process of rolling out a number of national e-health initiatives, including the National Electronic Health Record (NEHR). A critical enabler in the journey towards semantic interoperability is a Logical Information Model (LIM) that harmonises the semantics of the information structure with the terminology. The Singapore LIM uses a combination of international standards, including ISO 13606-1 (a reference model for electronic health record communication), ISO 21090 (healthcare datatypes), and SNOMED CT (healthcare terminology). The LIM is accompanied by a logical design approach, used to generate interoperability artifacts, and incorporates mechanisms for achieving unidirectional and bidirectional semantic interoperability.

Semantics, Pragmatics, and the Nature of Semantic Theories

ERIC Educational Resources Information Center

Spewak, David Charles, Jr.

2013-01-01

The primary concern of this dissertation is determining the distinction between semantics and pragmatics and how context sensitivity should be accommodated within a semantic theory. I approach the question over how to distinguish semantics from pragmatics from a new angle by investigating what the objects of a semantic theory are, namely…

Suggestion-Induced Modulation of Semantic Priming during Functional Magnetic Resonance Imaging

PubMed Central

Ulrich, Martin; Kiefer, Markus; Bongartz, Walter; Grön, Georg; Hoenig, Klaus

2015-01-01

Using functional magnetic resonance imaging during a primed visual lexical decision task, we investigated the neural and functional mechanisms underlying modulations of semantic word processing through hypnotic suggestions aimed at altering lexical processing of primes. The priming task was to discriminate between target words and pseudowords presented 200 ms after the prime word which was semantically related or unrelated to the target. In a counterbalanced study design, each participant performed the task once at normal wakefulness and once after the administration of hypnotic suggestions to perceive the prime as a meaningless symbol of a foreign language. Neural correlates of priming were defined as significantly lower activations upon semantically related compared to unrelated trials. We found significant suggestive treatment-induced reductions in neural priming, albeit irrespective of the degree of suggestibility. Neural priming was attenuated upon suggestive treatment compared with normal wakefulness in brain regions supporting automatic (fusiform gyrus) and controlled semantic processing (superior and middle temporal gyri, pre- and postcentral gyri, and supplementary motor area). Hence, suggestions reduced semantic word processing by conjointly dampening both automatic and strategic semantic processes. PMID:25923740

Dissociation of lexical syntax and semantics: evidence from focal cortical degeneration.

PubMed

Garrard, P; Carroll, E; Vinson, D; Vigliocco, G

2004-10-01

The question of whether information relevant to meaning (semantics) and structure (syntax) relies on a common language processor or on separate subsystems has proved difficult to address definitively because of the confounds involved in comparing the two types of information. At the sentence level syntactic and semantic judgments make different cognitive demands, while at the single word level, the most commonly used syntactic distinction (between nouns and verbs) is confounded with a fundamental semantic difference (between objects and actions). The present study employs a different syntactic contrast (between count nouns and mass nouns), which is crossed with a semantic difference (between naturally occurring and man-made substances) applying to words within a circumscribed semantic field (foodstuffs). We show, first, that grammaticality judgments of a patient with semantic dementia are indistinguishable from those of a group of age-matched controls, and are similar regardless of the status of his semantic knowledge about the item. In a second experiment we use the triadic task in a group of age-matched controls to show that similarity judgments are influenced not only by meaning (natural vs. manmade), but also implicitly by syntactic information (count vs. mass). Using the same task in a patient with semantic dementia we show that the semantic influences on the syntactic dimension are unlikely to account for this pattern in normals. These data are discussed in relation to modular vs. nonmodular models of language processing, and in particular to the semantic-syntactic distinction.

Semantic-based surveillance video retrieval.

PubMed

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Speed and Accuracy in the Processing of False Statements About Semantic Information.

ERIC Educational Resources Information Center

Ratcliff, Roger

1982-01-01

A standard reaction time procedure and a response signal procedure were used on data from eight experiments on semantic verifications. Results suggest that simple models of the semantic verification task that assume a single yes/no dimension on which discrimination is made are not correct. (Author/PN)

Knowledge Provenance in Semantic Wikis

NASA Astrophysics Data System (ADS)

Ding, L.; Bao, J.; McGuinness, D. L.

2008-12-01

Collaborative online environments with a technical Wiki infrastructure are becoming more widespread. One of the strengths of a Wiki environment is that it is relatively easy for numerous users to contribute original content and modify existing content (potentially originally generated by others). As more users begin to depend on informational content that is evolving by Wiki communities, it becomes more important to track the provenance of the information. Semantic Wikis expand upon traditional Wiki environments by adding some computationally understandable encodings of some of the terms and relationships in Wikis. We have developed a semantic Wiki environment that expands a semantic Wiki with provenance markup. Provenance of original contributions as well as modifications is encoded using the provenance markup component of the Proof Markup Language. The Wiki environment provides the provenance markup automatically, thus users are not required to make specific encodings of author, contribution date, and modification trail. Further, our Wiki environment includes a search component that understands the provenance primitives and thus can be used to provide a provenance-aware search facility. We will describe the knowledge provenance infrastructure of our Semantic Wiki and show how it is being used as the foundation of our group web site as well as a number of project web sites.

A computational modeling of semantic knowledge in reading comprehension: Integrating the landscape model with latent semantic analysis.

PubMed

Yeari, Menahem; van den Broek, Paul

2016-09-01

It is a well-accepted view that the prior semantic (general) knowledge that readers possess plays a central role in reading comprehension. Nevertheless, computational models of reading comprehension have not integrated the simulation of semantic knowledge and online comprehension processes under a unified mathematical algorithm. The present article introduces a computational model that integrates the landscape model of comprehension processes with latent semantic analysis representation of semantic knowledge. In three sets of simulations of previous behavioral findings, the integrated model successfully simulated the activation and attenuation of predictive and bridging inferences during reading, as well as centrality estimations and recall of textual information after reading. Analyses of the computational results revealed new theoretical insights regarding the underlying mechanisms of the various comprehension phenomena.

Semantic Similarity between Web Documents Using Ontology

NASA Astrophysics Data System (ADS)

Chahal, Poonam; Singh Tomer, Manjeet; Kumar, Suresh

2018-06-01

The World Wide Web is the source of information available in the structure of interlinked web pages. However, the procedure of extracting significant information with the assistance of search engine is incredibly critical. This is for the reason that web information is written mainly by using natural language, and further available to individual human. Several efforts have been made in semantic similarity computation between documents using words, concepts and concepts relationship but still the outcome available are not as per the user requirements. This paper proposes a novel technique for computation of semantic similarity between documents that not only takes concepts available in documents but also relationships that are available between the concepts. In our approach documents are being processed by making ontology of the documents using base ontology and a dictionary containing concepts records. Each such record is made up of the probable words which represents a given concept. Finally, document ontology's are compared to find their semantic similarity by taking the relationships among concepts. Relevant concepts and relations between the concepts have been explored by capturing author and user intention. The proposed semantic analysis technique provides improved results as compared to the existing techniques.

Semantic Similarity between Web Documents Using Ontology

NASA Astrophysics Data System (ADS)

Chahal, Poonam; Singh Tomer, Manjeet; Kumar, Suresh

2018-03-01

The World Wide Web is the source of information available in the structure of interlinked web pages. However, the procedure of extracting significant information with the assistance of search engine is incredibly critical. This is for the reason that web information is written mainly by using natural language, and further available to individual human. Several efforts have been made in semantic similarity computation between documents using words, concepts and concepts relationship but still the outcome available are not as per the user requirements. This paper proposes a novel technique for computation of semantic similarity between documents that not only takes concepts available in documents but also relationships that are available between the concepts. In our approach documents are being processed by making ontology of the documents using base ontology and a dictionary containing concepts records. Each such record is made up of the probable words which represents a given concept. Finally, document ontology's are compared to find their semantic similarity by taking the relationships among concepts. Relevant concepts and relations between the concepts have been explored by capturing author and user intention. The proposed semantic analysis technique provides improved results as compared to the existing techniques.

Semantic Knowledge for Famous Names in Mild Cognitive Impairment

PubMed Central

Seidenberg, Michael; Guidotti, Leslie; Nielson, Kristy A.; Woodard, John L.; Durgerian, Sally; Zhang, Qi; Gander, Amelia; Antuono, Piero; Rao, Stephen M.

2008-01-01

Person identification represents a unique category of semantic knowledge that is commonly impaired in Alzheimer's Disease (AD), but has received relatively little investigation in patients with Mild Cognitive Impairment (MCI). The current study examined the retrieval of semantic knowledge for famous names from three time epochs (recent, remote, and enduring) in two participant groups; 23 aMCI patients and 23 healthy elderly controls. The aMCI group was less accurate and produced less semantic knowledge than controls for famous names. Names from the enduring period were recognized faster than both recent and remote names in both groups, and remote names were recognized more quickly than recent names. Episodic memory performance was correlated with greater semantic knowledge particularly for recent names. We suggest that the anterograde memory deficits in the aMCI group interferes with learning of recent famous names and as a result produces difficulties with updating and integrating new semantic information with previously stored information. The implications of these findings for characterizing semantic memory deficits in MCI are discussed. PMID:19128524

Processing Coordinated Verb Phrases: The Relevance of Lexical-Semantic, Conceptual, and Contextual Information towards Establishing Verbal Parallelism

ERIC Educational Resources Information Center

Tutunjian, Damon A.

2010-01-01

This dissertation examines the influence of lexical-semantic representations, conceptual similarity, and contextual fit on the processing of coordinated verb phrases. The study integrates information gleaned from current linguistic theory with current psycholinguistic approaches to examining the processing of coordinated verb phrases. It has…

Semantic memory in developmental amnesia.

PubMed

Elward, Rachael L; Vargha-Khadem, Faraneh

2018-04-30

Patients with developmental amnesia resulting from bilateral hippocampal atrophy associated with neonatal hypoxia-ischaemia typically show relatively preserved semantic memory and factual knowledge about the natural world despite severe impairments in episodic memory. Understanding the neural and mnemonic processes that enable this context-free semantic knowledge to be acquired throughout development without the support of the contextualised episodic memory system is a serious challenge. This review describes the clinical presentation of patients with developmental amnesia, contrasts its features with those reported for adult-onset hippocampal amnesia, and analyses the effects of variables that influence the learning of new semantic information. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Neural correlates of semantic associations in patients with schizophrenia.

PubMed

Sass, Katharina; Heim, Stefan; Sachs, Olga; Straube, Benjamin; Schneider, Frank; Habel, Ute; Kircher, Tilo

2014-03-01

Patients with schizophrenia have semantic processing disturbances leading to expressive language deficits (formal thought disorder). The underlying pathology has been related to alterations in the semantic network and its neural correlates. Moreover, crossmodal processing, an important aspect of communication, is impaired in schizophrenia. Here we investigated specific processing abnormalities in patients with schizophrenia with regard to modality and semantic distance in a semantic priming paradigm. Fourteen patients with schizophrenia and fourteen demographically matched controls made visual lexical decisions on successively presented word-pairs (SOA = 350 ms) with direct or indirect relations, unrelated word-pairs, and pseudoword-target stimuli during fMRI measurement. Stimuli were presented in a unimodal (visual) or crossmodal (auditory-visual) fashion. On the neural level, the effect of semantic relation indicated differences (patients > controls) within the right angular gyrus and precuneus. The effect of modality revealed differences (controls > patients) within the left superior frontal, middle temporal, inferior occipital, right angular gyri, and anterior cingulate cortex. Semantic distance (direct vs. indirect) induced distinct activations within the left middle temporal, fusiform gyrus, right precuneus, and thalamus with patients showing fewer differences between direct and indirect word-pairs. The results highlight aberrant priming-related brain responses in patients with schizophrenia. Enhanced activation for patients possibly reflects deficits in semantic processes that might be caused by a delayed and enhanced spread of activation within the semantic network. Modality-specific decreases of activation in patients might be related to impaired perceptual integration. Those deficits could induce and increase the prominent symptoms of schizophrenia like impaired speech processing.

Semantic-gap-oriented active learning for multilabel image annotation.

PubMed

Tang, Jinhui; Zha, Zheng-Jun; Tao, Dacheng; Chua, Tat-Seng

2012-04-01

User interaction is an effective way to handle the semantic gap problem in image annotation. To minimize user effort in the interactions, many active learning methods were proposed. These methods treat the semantic concepts individually or correlatively. However, they still neglect the key motivation of user feedback: to tackle the semantic gap. The size of the semantic gap of each concept is an important factor that affects the performance of user feedback. User should pay more efforts to the concepts with large semantic gaps, and vice versa. In this paper, we propose a semantic-gap-oriented active learning method, which incorporates the semantic gap measure into the information-minimization-based sample selection strategy. The basic learning model used in the active learning framework is an extended multilabel version of the sparse-graph-based semisupervised learning method that incorporates the semantic correlation. Extensive experiments conducted on two benchmark image data sets demonstrated the importance of bringing the semantic gap measure into the active learning process.

Semantic transparency affects morphological priming . . . eventually.

PubMed

Heyer, Vera; Kornishova, Dana

2018-05-01

Semantic transparency has been in the focus of psycholinguistic research for decades, with the controversy about the time course of the application of morpho-semantic information during the processing of morphologically complex words not yet resolved. This study reports two masked priming studies with English - ness and Russian - ost' nominalisations, investigating how semantic transparency modulates native speakers' morphological priming effects at short and long stimulus onset asynchronies (SOAs). In both languages, we found increased morphological priming for nominalisations at the transparent end of the scale (e.g. paleness - pale) in comparison to items at the opaque end of the scale (e.g. business - busy) but only at longer prime durations. The present findings are in line with models that posit an initial phase of morpho-orthographic (semantically blind) decomposition.

Software analysis in the semantic web

NASA Astrophysics Data System (ADS)

Taylor, Joshua; Hall, Robert T.

2013-05-01

Many approaches in software analysis, particularly dynamic malware analyis, benefit greatly from the use of linked data and other Semantic Web technology. In this paper, we describe AIS, Inc.'s Semantic Extractor (SemEx) component from the Malware Analysis and Attribution through Genetic Information (MAAGI) effort, funded under DARPA's Cyber Genome program. The SemEx generates OWL-based semantic models of high and low level behaviors in malware samples from system call traces generated by AIS's introspective hypervisor, IntroVirtTM. Within MAAGI, these semantic models were used by modules that cluster malware samples by functionality, and construct "genealogical" malware lineages. Herein, we describe the design, implementation, and use of the SemEx, as well as the C2DB, an OWL ontology used for representing software behavior and cyber-environments.

Elaborative Retrieval: Do Semantic Mediators Improve Memory?

ERIC Educational Resources Information Center

Lehman, Melissa; Karpicke, Jeffrey D.

2016-01-01

The elaborative retrieval account of retrieval-based learning proposes that retrieval enhances retention because the retrieval process produces the generation of semantic mediators that link cues to target information. We tested 2 assumptions that form the basis of this account: that semantic mediators are more likely to be generated during…

A model-driven approach for representing clinical archetypes for Semantic Web environments.

PubMed

Martínez-Costa, Catalina; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás; Maldonado, José Alberto

2009-02-01

The life-long clinical information of any person supported by electronic means configures his Electronic Health Record (EHR). This information is usually distributed among several independent and heterogeneous systems that may be syntactically or semantically incompatible. There are currently different standards for representing and exchanging EHR information among different systems. In advanced EHR approaches, clinical information is represented by means of archetypes. Most of these approaches use the Archetype Definition Language (ADL) to specify archetypes. However, ADL has some drawbacks when attempting to perform semantic activities in Semantic Web environments. In this work, Semantic Web technologies are used to specify clinical archetypes for advanced EHR architectures. The advantages of using the Ontology Web Language (OWL) instead of ADL are described and discussed in this work. Moreover, a solution combining Semantic Web and Model-driven Engineering technologies is proposed to transform ADL into OWL for the CEN EN13606 EHR architecture.

Rule-based support system for multiple UMLS semantic type assignments

PubMed Central

Geller, James; He, Zhe; Perl, Yehoshua; Morrey, C. Paul; Xu, Julia

2012-01-01

Background When new concepts are inserted into the UMLS, they are assigned one or several semantic types from the UMLS Semantic Network by the UMLS editors. However, not every combination of semantic types is permissible. It was observed that many concepts with rare combinations of semantic types have erroneous semantic type assignments or prohibited combinations of semantic types. The correction of such errors is resource-intensive. Objective We design a computational system to inform UMLS editors as to whether a specific combination of two, three, four, or five semantic types is permissible or prohibited or questionable. Methods We identify a set of inclusion and exclusion instructions in the UMLS Semantic Network documentation and derive corresponding rule-categories as well as rule-categories from the UMLS concept content. We then design an algorithm adviseEditor based on these rule-categories. The algorithm specifies rules for an editor how to proceed when considering a tuple (pair, triple, quadruple, quintuple) of semantic types to be assigned to a concept. Results Eight rule-categories were identified. A Web-based system was developed to implement the adviseEditor algorithm, which returns for an input combination of semantic types whether it is permitted, prohibited or (in a few cases) requires more research. The numbers of semantic type pairs assigned to each rule-category are reported. Interesting examples for each rule-category are illustrated. Cases of semantic type assignments that contradict rules are listed, including recently introduced ones. Conclusion The adviseEditor system implements explicit and implicit knowledge available in the UMLS in a system that informs UMLS editors about the permissibility of a desired combination of semantic types. Using adviseEditor might help accelerate the work of the UMLS editors and prevent erroneous semantic type assignments. PMID:23041716

Approaching semantic interoperability in Health Level Seven

PubMed Central

Alschuler, Liora

2010-01-01

‘Semantic Interoperability’ is a driving objective behind many of Health Level Seven's standards. The objective in this paper is to take a step back, and consider what semantic interoperability means, assess whether or not it has been achieved, and, if not, determine what concrete next steps can be taken to get closer. A framework for measuring semantic interoperability is proposed, using a technique called the ‘Single Logical Information Model’ framework, which relies on an operational definition of semantic interoperability and an understanding that interoperability improves incrementally. Whether semantic interoperability tomorrow will enable one computer to talk to another, much as one person can talk to another person, is a matter for speculation. It is assumed, however, that what gets measured gets improved, and in that spirit this framework is offered as a means to improvement. PMID:21106995

Semantic bifurcated importance field visualization

NASA Astrophysics Data System (ADS)

Lindahl, Eric; Petrov, Plamen

2007-04-01

While there are many good ways to map sensual reality to two dimensional displays, mapping non-physical and possibilistic information can be challenging. The advent of faster-than-real-time systems allow the predictive and possibilistic exploration of important factors that can affect the decision maker. Visualizing a compressed picture of the past and possible factors can assist the decision maker summarizing information in a cognitive based model thereby reducing clutter and perhaps related decision times. Our proposed semantic bifurcated importance field visualization uses saccadic eye motion models to partition the display into a possibilistic and sensed data vertically and spatial and semantic data horizontally. Saccadic eye movement precedes and prepares decision makers before nearly every directed action. Cognitive models for saccadic eye movement show that people prefer lateral to vertical saccadic movement. Studies have suggested that saccades may be coupled to momentary problem solving strategies. Also, the central 1.5 degrees of the visual field represents 100 times greater resolution that then peripheral field so concentrating factors can reduce unnecessary saccades. By packing information according to saccadic models, we can relate important decision factors reduce factor dimensionality and present the dense summary dimensions of semantic and importance. Inter and intra ballistics of the SBIFV provide important clues on how semantic packing assists in decision making. Future directions of SBIFV are to make the visualization reactive and conformal to saccades specializing targets to ballistics, such as dynamically filtering and highlighting verbal targets for left saccades and spatial targets for right saccades.

Semantics vs Pragmatics of a Compound Word

ERIC Educational Resources Information Center

Smirnova, Elena A.; Biktemirova, Ella I.; Davletbaeva, Diana N.

2016-01-01

This paper is devoted to the study of correlation between semantic and pragmatic potential of a compound word, which functions in informal speech, and the mechanisms of secondary nomination, which realizes the potential of semantic-pragmatic features of colloquial compounds. The relevance and the choice of the research question is based on the…

Learning the Semantics of Structured Data Sources

ERIC Educational Resources Information Center

Taheriyan, Mohsen

2015-01-01

Information sources such as relational databases, spreadsheets, XML, JSON, and Web APIs contain a tremendous amount of structured data, however, they rarely provide a semantic model to describe their contents. Semantic models of data sources capture the intended meaning of data sources by mapping them to the concepts and relationships defined by a…

A Semantic Web-based System for Managing Clinical Archetypes.

PubMed

Fernandez-Breis, Jesualdo Tomas; Menarguez-Tortosa, Marcos; Martinez-Costa, Catalina; Fernandez-Breis, Eneko; Herrero-Sempere, Jose; Moner, David; Sanchez, Jesus; Valencia-Garcia, Rafael; Robles, Montserrat

2008-01-01

Archetypes facilitate the sharing of clinical knowledge and therefore are a basic tool for achieving interoperability between healthcare information systems. In this paper, a Semantic Web System for Managing Archetypes is presented. This system allows for the semantic annotation of archetypes, as well for performing semantic searches. The current system is capable of working with both ISO13606 and OpenEHR archetypes.

Memory for the perceptual and semantic attributes of information in pure amnesic and severe closed-head injured patients.

PubMed

Carlesimo, Giovanni A; Bonanni, Rita; Caltagirone, Carlo

2003-05-01

This study investigated the hypothesis that brain damaged patients with memory disorder are poorer at remembering the semantic than the perceptual attributes of information. Eight patients with memory impairment of different etiology and 24 patients with chronic consequences of severe closed-head injury were compared to similarly sized age- and literacy-matched normal control groups on recognition tests for the physical aspect and the semantic identity of words and pictures lists. In order to avoid interpretative problems deriving from different absolute levels of performance, study conditions were manipulated across subjects to obtain comparable accuracy on the perceptual recognition tests in the memory disordered and control groups. The results of the Picture Recognition test were consistent with the hypothesis. Indeed, having more time for the stimulus encoding, the two memory disordered groups performed at the same level as the normal subjects on the perceptual test but significantly lower on the semantic test. Instead, on the Word Recognition test, following study condition manipulation, patients and controls performed similarly on both the perceptual and the semantic tests. These data only partially support the hypothesis of the study; rather they suggest that in memory disordered patients there is a reduction of the advantage, exhibited by normal controls, of retrieving pictures over words (picture superiority effect).

CNTRO: A Semantic Web Ontology for Temporal Relation Inferencing in Clinical Narratives.

PubMed

Tao, Cui; Wei, Wei-Qi; Solbrig, Harold R; Savova, Guergana; Chute, Christopher G

2010-11-13

Using Semantic-Web specifications to represent temporal information in clinical narratives is an important step for temporal reasoning and answering time-oriented queries. Existing temporal models are either not compatible with the powerful reasoning tools developed for the Semantic Web, or designed only for structured clinical data and therefore are not ready to be applied on natural-language-based clinical narrative reports directly. We have developed a Semantic-Web ontology which is called Clinical Narrative Temporal Relation ontology. Using this ontology, temporal information in clinical narratives can be represented as RDF (Resource Description Framework) triples. More temporal information and relations can then be inferred by Semantic-Web based reasoning tools. Experimental results show that this ontology can represent temporal information in real clinical narratives successfully.

iSMART: Ontology-based Semantic Query of CDA Documents

PubMed Central

Liu, Shengping; Ni, Yuan; Mei, Jing; Li, Hanyu; Xie, Guotong; Hu, Gang; Liu, Haifeng; Hou, Xueqiao; Pan, Yue

2009-01-01

The Health Level 7 Clinical Document Architecture (CDA) is widely accepted as the format for electronic clinical document. With the rich ontological references in CDA documents, the ontology-based semantic query could be performed to retrieve CDA documents. In this paper, we present iSMART (interactive Semantic MedicAl Record reTrieval), a prototype system designed for ontology-based semantic query of CDA documents. The clinical information in CDA documents will be extracted into RDF triples by a declarative XML to RDF transformer. An ontology reasoner is developed to infer additional information by combining the background knowledge from SNOMED CT ontology. Then an RDF query engine is leveraged to enable the semantic queries. This system has been evaluated using the real clinical documents collected from a large hospital in southern China. PMID:20351883

Semantic Segmentation of Indoor Point Clouds Using Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Babacan, K.; Chen, L.; Sohn, G.

2017-11-01

As Building Information Modelling (BIM) thrives, geometry becomes no longer sufficient; an ever increasing variety of semantic information is needed to express an indoor model adequately. On the other hand, for the existing buildings, automatically generating semantically enriched BIM from point cloud data is in its infancy. The previous research to enhance the semantic content rely on frameworks in which some specific rules and/or features that are hand coded by specialists. These methods immanently lack generalization and easily break in different circumstances. On this account, a generalized framework is urgently needed to automatically and accurately generate semantic information. Therefore we propose to employ deep learning techniques for the semantic segmentation of point clouds into meaningful parts. More specifically, we build a volumetric data representation in order to efficiently generate the high number of training samples needed to initiate a convolutional neural network architecture. The feedforward propagation is used in such a way to perform the classification in voxel level for achieving semantic segmentation. The method is tested both for a mobile laser scanner point cloud, and a larger scale synthetically generated data. We also demonstrate a case study, in which our method can be effectively used to leverage the extraction of planar surfaces in challenging cluttered indoor environments.

An fMRI-study on semantic priming of panic-related information in depression without comorbid anxiety.

PubMed

Sass, Katharina; Kircher, Tilo; Gauggel, Siegfried; Habel, Ute

2014-04-30

Depression often involves anxiety symptoms and shows a strong comorbidity with panic disorder. However, the neural basis is unclear. The aim of the current study was to use semantic priming to investigate the neural correlates of panic and anxiety-related information processing in depression. In a lexical decision task, panic/agoraphobia-disorder-related and neutral word-pairs were presented during functional magnetic resonance imaging. Participants comprised 19 patients with major depression but without comorbid anxiety and 19 demographically matched controls. On a behavioral level, comparable significant priming effects were found for the neutral condition, while only patients showed a significant inhibition effect (slower reaction time for panic-related stimuli) for the panic condition. On a neural level, significant group differences emerged in left fronto-parietal (enhanced activation for patients) and left temporo-occipital regions (reduced activation for patients). The results showed that depressed patients recruit not only areas related to the interaction of emotion and semantic processing but also regions that are related to fear circuitry to process panic-related information. Hence, in the context of depression, there seems to be a pathological processing of panic-related information that could play an important role during the disorder and should be considered. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Semantic-episodic interactions in the neuropsychology of disbelief.

PubMed

Ladowsky-Brooks, Ricki; Alcock, James E

2007-03-01

The purpose of this paper is to outline ways in which characteristics of memory functioning determine truth judgements regarding verbally transmitted information. Findings on belief formation from several areas of psychology were reviewed in order to identify general principles that appear to underlie the designation of information in memory as "true" or "false". Studies on belief formation have demonstrated that individuals have a tendency to encode information as "true" and that an additional encoding step is required to tag information as "false". This additional step can involve acquisition and later recall of semantic-episodic associations between message content and contextual cues that signal that information is "false". Semantic-episodic interactions also appear to prevent new information from being accepted as "true" through encoding bias or the assignment of a "false" tag to data that is incompatible with prior knowledge. It is proposed that truth judgements are made through a combined weighting of the reliability of the information source and the compatibility of this information with already stored data. This requires interactions in memory. Failure to integrate different types of memories, such as semantic and episodic memories, can arise from mild hippocampal dysfunction and might result in delusions.

Lack of semantic priming effects in famous person recognition in Mild Cognitive Impairment.

PubMed

Brambati, Simona M; Peters, Frédéric; Belleville, Sylvie; Joubert, Sven

2012-04-01

Growing evidence indicates that individuals with Mild Cognitive Impairment (MCI) manifest semantic deficits that are often more severe for items that are characterized by a unique semantic and lexical association, such as famous people and famous buildings, than common concepts, such as objects. However, it is still controversial whether the semantic deficits observed in MCI are determined by a degradation of semantic information or by a deficit in intentional access to semantic knowledge. Here we used a semantic priming task in order to assess the integrity of the semantic system without requiring explicit access to this system. This paradigm may provide new insights in clarifying the nature of the semantic deficits in MCI. We assessed the semantic and repetition priming effect in 13 individuals with MCI and 13 age-matched controls who engaged in a familiarity judgment task of famous names. In the semantic priming condition, the prime was the name of a member of the same occupation category as the target (Tom Cruise-Brad Pitt), while in the repetition priming condition the prime was the same name as the target (Charlie Chaplin-Charlie Chaplin). The results showed a defective priming effect in MCI in the semantic but not in the repetition priming condition. Specifically, when compared to controls, MCI patients did not show a facilitation effect in responding to the same occupation prime-target pairs, but they showed an equivalent facilitation effect when the target was the same name as the prime. The present results provide support to the hypothesis that the semantic impairments observed in MCI cannot be uniquely ascribed to a deficit in intentional access to semantic information. Instead, these findings point to the semantic nature of these deficits and, in particular, to a degraded representation of semantic information concerning famous people. Copyright © 2011 Elsevier Srl. All rights reserved.

Semantic Context Detection Using Audio Event Fusion

NASA Astrophysics Data System (ADS)

Chu, Wei-Ta; Cheng, Wen-Huang; Wu, Ja-Ling

2006-12-01

Semantic-level content analysis is a crucial issue in achieving efficient content retrieval and management. We propose a hierarchical approach that models audio events over a time series in order to accomplish semantic context detection. Two levels of modeling, audio event and semantic context modeling, are devised to bridge the gap between physical audio features and semantic concepts. In this work, hidden Markov models (HMMs) are used to model four representative audio events, that is, gunshot, explosion, engine, and car braking, in action movies. At the semantic context level, generative (ergodic hidden Markov model) and discriminative (support vector machine (SVM)) approaches are investigated to fuse the characteristics and correlations among audio events, which provide cues for detecting gunplay and car-chasing scenes. The experimental results demonstrate the effectiveness of the proposed approaches and provide a preliminary framework for information mining by using audio characteristics.

Context-rich semantic framework for effective data-to-decisions in coalition networks

NASA Astrophysics Data System (ADS)

Grueneberg, Keith; de Mel, Geeth; Braines, Dave; Wang, Xiping; Calo, Seraphin; Pham, Tien

2013-05-01

In a coalition context, data fusion involves combining of soft (e.g., field reports, intelligence reports) and hard (e.g., acoustic, imagery) sensory data such that the resulting output is better than what it would have been if the data are taken individually. However, due to the lack of explicit semantics attached with such data, it is difficult to automatically disseminate and put the right contextual data in the hands of the decision makers. In order to understand the data, explicit meaning needs to be added by means of categorizing and/or classifying the data in relationship to each other from base reference sources. In this paper, we present a semantic framework that provides automated mechanisms to expose real-time raw data effectively by presenting appropriate information needed for a given situation so that an informed decision could be made effectively. The system utilizes controlled natural language capabilities provided by the ITA (International Technology Alliance) Controlled English (CE) toolkit to provide a human-friendly semantic representation of messages so that the messages can be directly processed in human/machine hybrid environments. The Real-time Semantic Enrichment (RTSE) service adds relevant contextual information to raw data streams from domain knowledge bases using declarative rules. The rules define how the added semantics and context information are derived and stored in a semantic knowledge base. The software framework exposes contextual information from a variety of hard and soft data sources in a fast, reliable manner so that an informed decision can be made using semantic queries in intelligent software systems.

Comprehensive Analysis of Semantic Web Reasoners and Tools: A Survey

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2017-01-01

Ontologies are emerging as best representation techniques for knowledge based context domains. The continuing need for interoperation, collaboration and effective information retrieval has lead to the creation of semantic web with the help of tools and reasoners which manages personalized information. The future of semantic web lies in an ontology…

Semantic associative relations and conceptual processing.

PubMed

Di Giacomo, Dina; De Federicis, Lucia Serenella; Pistelli, Manuela; Fiorenzi, Daniela; Passafiume, Domenico

2012-02-01

We analysed the organisation of semantic network using associative mechanisms between different types of information and studied the progression of the use of these associative relations during development. We aimed to verify the linkage of concepts with the use of semantic associative relations. The goal of this study was to analyse the cognitive ability to use associative relations between various items when describing old and/or new concepts. We examined the performance of 100 subjects between the ages of 4 and 7 years on an experimental task using five associative relations based on verbal encoding. The results showed that children are able to use the five semantic associative relations at age 4, but performance with each of the different associative relations improves at different times during development. Functional and part/whole relations develop at an early age, whereas the superordinate relations develop later. Our study clarified the characteristics of the progression of semantic associations during development as well as the roles that associative relations play in the structure and improvement of the semantic store.

The semantic and episodic subcomponents of famous person knowledge: dissociation in healthy subjects.

PubMed

Piolino, Pascale; Lamidey, Virginie; Desgranges, Béatrice; Eustache, Francis

2007-01-01

Fifty-two subjects between ages 40 and 79 years were administered a questionnaire assessing their ability to recall semantic information about famous people from 4 different decades and to recollect its episodic source of acquisition together with autonoetic consciousness via the remember-know paradigm. In addition, they underwent a battery of standardized neuropsychological tests to assess episodic and semantic memory and executive functions. The analyses of age reveal differences for the episodic source score but no differences between age groups for the semantic scores within each decade. Regardless of the age of people, the analyses also show that semantic memory subcomponents of the famous person test are highly associated with each other as well as with the source component. The recall of semantic information on the famous person test relies on participants' semantic abilities, whereas the recall of its episodic source depends on their executive functions. The present findings confirm the existence of an episodic-semantic distinction in knowledge about famous people. They provide further evidence that personal source and semantic information are at once distinct and highly interactive within the framework of remote memory. (c) 2007 APA, all rights reserved.

SCALEUS: Semantic Web Services Integration for Biomedical Applications.

PubMed

Sernadela, Pedro; González-Castro, Lorena; Oliveira, José Luís

2017-04-01

In recent years, we have witnessed an explosion of biological data resulting largely from the demands of life science research. The vast majority of these data are freely available via diverse bioinformatics platforms, including relational databases and conventional keyword search applications. This type of approach has achieved great results in the last few years, but proved to be unfeasible when information needs to be combined or shared among different and scattered sources. During recent years, many of these data distribution challenges have been solved with the adoption of semantic web. Despite the evident benefits of this technology, its adoption introduced new challenges related with the migration process, from existent systems to the semantic level. To facilitate this transition, we have developed Scaleus, a semantic web migration tool that can be deployed on top of traditional systems in order to bring knowledge, inference rules, and query federation to the existent data. Targeted at the biomedical domain, this web-based platform offers, in a single package, straightforward data integration and semantic web services that help developers and researchers in the creation process of new semantically enhanced information systems. SCALEUS is available as open source at http://bioinformatics-ua.github.io/scaleus/ .

Enhancing biomedical text summarization using semantic relation extraction.

PubMed

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

Enhancing Biomedical Text Summarization Using Semantic Relation Extraction

PubMed Central

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization. PMID:21887336

Semantics of the visual environment encoded in parahippocampal cortex

PubMed Central

Bonner, Michael F.; Price, Amy Rose; Peelle, Jonathan E.; Grossman, Murray

2016-01-01

Semantic representations capture the statistics of experience and store this information in memory. A fundamental component of this memory system is knowledge of the visual environment, including knowledge of objects and their associations. Visual semantic information underlies a range of behaviors, from perceptual categorization to cognitive processes such as language and reasoning. Here we examine the neuroanatomic system that encodes visual semantics. Across three experiments, we found converging evidence indicating that knowledge of verbally mediated visual concepts relies on information encoded in a region of the ventral-medial temporal lobe centered on parahippocampal cortex. In an fMRI study, this region was strongly engaged by the processing of concepts relying on visual knowledge but not by concepts relying on other sensory modalities. In a study of patients with the semantic variant of primary progressive aphasia (semantic dementia), atrophy that encompassed this region was associated with a specific impairment in verbally mediated visual semantic knowledge. Finally, in a structural study of healthy adults from the fMRI experiment, gray matter density in this region related to individual variability in the processing of visual concepts. The anatomic location of these findings aligns with recent work linking the ventral-medial temporal lobe with high-level visual representation, contextual associations, and reasoning through imagination. Together this work suggests a critical role for parahippocampal cortex in linking the visual environment with knowledge systems in the human brain. PMID:26679216

Semantics of the Visual Environment Encoded in Parahippocampal Cortex.

PubMed

Bonner, Michael F; Price, Amy Rose; Peelle, Jonathan E; Grossman, Murray

2016-03-01

Semantic representations capture the statistics of experience and store this information in memory. A fundamental component of this memory system is knowledge of the visual environment, including knowledge of objects and their associations. Visual semantic information underlies a range of behaviors, from perceptual categorization to cognitive processes such as language and reasoning. Here we examine the neuroanatomic system that encodes visual semantics. Across three experiments, we found converging evidence indicating that knowledge of verbally mediated visual concepts relies on information encoded in a region of the ventral-medial temporal lobe centered on parahippocampal cortex. In an fMRI study, this region was strongly engaged by the processing of concepts relying on visual knowledge but not by concepts relying on other sensory modalities. In a study of patients with the semantic variant of primary progressive aphasia (semantic dementia), atrophy that encompassed this region was associated with a specific impairment in verbally mediated visual semantic knowledge. Finally, in a structural study of healthy adults from the fMRI experiment, gray matter density in this region related to individual variability in the processing of visual concepts. The anatomic location of these findings aligns with recent work linking the ventral-medial temporal lobe with high-level visual representation, contextual associations, and reasoning through imagination. Together, this work suggests a critical role for parahippocampal cortex in linking the visual environment with knowledge systems in the human brain.

Ontology-based knowledge representation for resolution of semantic heterogeneity in GIS

NASA Astrophysics Data System (ADS)

Liu, Ying; Xiao, Han; Wang, Limin; Han, Jialing

2017-07-01

Lack of semantic interoperability in geographical information systems has been identified as the main obstacle for data sharing and database integration. The new method should be found to overcome the problems of semantic heterogeneity. Ontologies are considered to be one approach to support geographic information sharing. This paper presents an ontology-driven integration approach to help in detecting and possibly resolving semantic conflicts. Its originality is that each data source participating in the integration process contains an ontology that defines the meaning of its own data. This approach ensures the automation of the integration through regulation of semantic integration algorithm. Finally, land classification in field GIS is described as the example.

Semantic annotation in biomedicine: the current landscape.

PubMed

Jovanović, Jelena; Bagheri, Ebrahim

2017-09-22

The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical documents with machine intelligible semantics facilitates advanced, semantics-based text management, curation, indexing, and search. This paper focuses on annotation of biomedical entity mentions with concepts from relevant biomedical knowledge bases such as UMLS. As a result, the meaning of those mentions is unambiguously and explicitly defined, and thus made readily available for automated processing. This process is widely known as semantic annotation, and the tools that perform it are known as semantic annotators.Over the last dozen years, the biomedical research community has invested significant efforts in the development of biomedical semantic annotation technology. Aiming to establish grounds for further developments in this area, we review a selected set of state of the art biomedical semantic annotators, focusing particularly on general purpose annotators, that is, semantic annotation tools that can be customized to work with texts from any area of biomedicine. We also examine potential directions for further improvements of today's annotators which could make them even more capable of meeting the needs of real-world applications. To motivate and encourage further developments in this area, along the suggested and/or related directions, we review existing and potential practical applications and benefits of semantic annotators.

Semantic Location Extraction from Crowdsourced Data

NASA Astrophysics Data System (ADS)

Koswatte, S.; Mcdougall, K.; Liu, X.

2016-06-01

Crowdsourced Data (CSD) has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network). This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction.

Semantic preview benefit during reading.

PubMed

Hohenstein, Sven; Kliegl, Reinhold

2014-01-01

Word features in parafoveal vision influence eye movements during reading. The question of whether readers extract semantic information from parafoveal words was studied in 3 experiments by using a gaze-contingent display change technique. Subjects read German sentences containing 1 of several preview words that were replaced by a target word during the saccade to the preview (boundary paradigm). In the 1st experiment the preview word was semantically related or unrelated to the target. Fixation durations on the target were shorter for semantically related than unrelated previews, consistent with a semantic preview benefit. In the 2nd experiment, half the sentences were presented following the rules of German spelling (i.e., previews and targets were printed with an initial capital letter), and the other half were presented completely in lowercase. A semantic preview benefit was obtained under both conditions. In the 3rd experiment, we introduced 2 further preview conditions, an identical word and a pronounceable nonword, while also manipulating the text contrast. Whereas the contrast had negligible effects, fixation durations on the target were reliably different for all 4 types of preview. Semantic preview benefits were greater for pretarget fixations closer to the boundary (large preview space) and, although not as consistently, for long pretarget fixation durations (long preview time). The results constrain theoretical proposals about eye movement control in reading. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

A DNA-based semantic fusion model for remote sensing data.

PubMed

Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H

2013-01-01

Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

A DNA-Based Semantic Fusion Model for Remote Sensing Data

PubMed Central

Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H.

2013-01-01

Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology. PMID:24116207

Preserved semantic priming effect in alexia.

PubMed

Mimura, M; Goodglass, H; Milberg, W

1996-09-01

BH, a left-handed patient with alexia and nonfluent aphasia, was presented with a lexical-decision task in which words and pronounceable pseudowords were preceded by semantically related or unrelated picture primes (Experiment 1). In Experiment 2, BH was given an explicit reading task using the word lists from Experiment 1. Performance on Experiment 2 disclosed severe reading deficits in both oral reading and semantic matching of the words to pictures. However, in Experiment 1, BH demonstrated a significant semantic priming effect, responding more accurately and more quickly to words preceded by related primes than by unrelated primes. The present results suggest that even in a patient with severe alexia, implicit access to semantic information can be preserved in the absence of explicit identification. The possibility of categorical gradient in implicit activation (living vs. nonliving) in BH was also discussed, which, however, needs to be clarified in the further investigation.

Semantic attributes are encoded in human electrocorticographic signals during visual object recognition.

PubMed

Rupp, Kyle; Roos, Matthew; Milsap, Griffin; Caceres, Carlos; Ratto, Christopher; Chevillet, Mark; Crone, Nathan E; Wolmetz, Michael

2017-03-01

Non-invasive neuroimaging studies have shown that semantic category and attribute information are encoded in neural population activity. Electrocorticography (ECoG) offers several advantages over non-invasive approaches, but the degree to which semantic attribute information is encoded in ECoG responses is not known. We recorded ECoG while patients named objects from 12 semantic categories and then trained high-dimensional encoding models to map semantic attributes to spectral-temporal features of the task-related neural responses. Using these semantic attribute encoding models, untrained objects were decoded with accuracies comparable to whole-brain functional Magnetic Resonance Imaging (fMRI), and we observed that high-gamma activity (70-110Hz) at basal occipitotemporal electrodes was associated with specific semantic dimensions (manmade-animate, canonically large-small, and places-tools). Individual patient results were in close agreement with reports from other imaging modalities on the time course and functional organization of semantic processing along the ventral visual pathway during object recognition. The semantic attribute encoding model approach is critical for decoding objects absent from a training set, as well as for studying complex semantic encodings without artificially restricting stimuli to a small number of semantic categories. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Concealed semantic and episodic autobiographical memory electrified.

PubMed

Ganis, Giorgio; Schendan, Haline E

2012-01-01

Electrophysiology-based concealed information tests (CIT) try to determine whether somebody possesses concealed information about a crime-related item (probe) by comparing event-related potentials (ERPs) between this item and comparison items (irrelevants). Although the broader field is sometimes referred to as "memory detection," little attention has been paid to the precise type of underlying memory involved. This study begins addressing this issue by examining the key distinction between semantic and episodic memory in the autobiographical domain within a CIT paradigm. This study also addresses the issue of whether multiple repetitions of the items over the course of the session habituate the brain responses. Participants were tested in a 3-stimulus CIT with semantic autobiographical probes (their own date of birth) and episodic autobiographical probes (a secret date learned just before the study). Results dissociated these two memory conditions on several ERP components. Semantic probes elicited a smaller frontal N2 than episodic probes, consistent with the idea that the frontal N2 decreases with greater pre-existing knowledge about the item. Likewise, semantic probes elicited a smaller central N400 than episodic probes. Semantic probes also elicited a larger P3b than episodic probes because of their richer meaning. In contrast, episodic probes elicited a larger late positive complex (LPC) than semantic probes, because of the recent episodic memory associated with them. All these ERPs showed a difference between probes and irrelevants in both memory conditions, except for the N400, which showed a difference only in the semantic condition. Finally, although repetition affected the ERPs, it did not reduce the difference between probes and irrelevants. These findings show that the type of memory associated with a probe has both theoretical and practical importance for CIT research.

Concealed semantic and episodic autobiographical memory electrified

PubMed Central

Ganis, Giorgio; Schendan, Haline E.

2013-01-01

Electrophysiology-based concealed information tests (CIT) try to determine whether somebody possesses concealed information about a crime-related item (probe) by comparing event-related potentials (ERPs) between this item and comparison items (irrelevants). Although the broader field is sometimes referred to as “memory detection,” little attention has been paid to the precise type of underlying memory involved. This study begins addressing this issue by examining the key distinction between semantic and episodic memory in the autobiographical domain within a CIT paradigm. This study also addresses the issue of whether multiple repetitions of the items over the course of the session habituate the brain responses. Participants were tested in a 3-stimulus CIT with semantic autobiographical probes (their own date of birth) and episodic autobiographical probes (a secret date learned just before the study). Results dissociated these two memory conditions on several ERP components. Semantic probes elicited a smaller frontal N2 than episodic probes, consistent with the idea that the frontal N2 decreases with greater pre-existing knowledge about the item. Likewise, semantic probes elicited a smaller central N400 than episodic probes. Semantic probes also elicited a larger P3b than episodic probes because of their richer meaning. In contrast, episodic probes elicited a larger late positive complex (LPC) than semantic probes, because of the recent episodic memory associated with them. All these ERPs showed a difference between probes and irrelevants in both memory conditions, except for the N400, which showed a difference only in the semantic condition. Finally, although repetition affected the ERPs, it did not reduce the difference between probes and irrelevants. These findings show that the type of memory associated with a probe has both theoretical and practical importance for CIT research. PMID:23355816

Developing A Web-based User Interface for Semantic Information Retrieval

NASA Technical Reports Server (NTRS)

Berrios, Daniel C.; Keller, Richard M.

2003-01-01

While there are now a number of languages and frameworks that enable computer-based systems to search stored data semantically, the optimal design for effective user interfaces for such systems is still uncle ar. Such interfaces should mask unnecessary query detail from users, yet still allow them to build queries of arbitrary complexity without significant restrictions. We developed a user interface supporting s emantic query generation for Semanticorganizer, a tool used by scient ists and engineers at NASA to construct networks of knowledge and dat a. Through this interface users can select node types, node attribute s and node links to build ad-hoc semantic queries for searching the S emanticOrganizer network.

Towards semantic interoperability for electronic health records.

PubMed

Garde, Sebastian; Knaup, Petra; Hovenga, Evelyn; Heard, Sam

2007-01-01

In the field of open electronic health records (EHRs), openEHR as an archetype-based approach is being increasingly recognised. It is the objective of this paper to shortly describe this approach, and to analyse how openEHR archetypes impact on health professionals and semantic interoperability. Analysis of current approaches to EHR systems, terminology and standards developments. In addition to literature reviews, we organised face-to-face and additional telephone interviews and tele-conferences with members of relevant organisations and committees. The openEHR archetypes approach enables syntactic interoperability and semantic interpretability -- both important prerequisites for semantic interoperability. Archetypes enable the formal definition of clinical content by clinicians. To enable comprehensive semantic interoperability, the development and maintenance of archetypes needs to be coordinated internationally and across health professions. Domain knowledge governance comprises a set of processes that enable the creation, development, organisation, sharing, dissemination, use and continuous maintenance of archetypes. It needs to be supported by information technology. To enable EHRs, semantic interoperability is essential. The openEHR archetypes approach enables syntactic interoperability and semantic interpretability. However, without coordinated archetype development and maintenance, 'rank growth' of archetypes would jeopardize semantic interoperability. We therefore believe that openEHR archetypes and domain knowledge governance together create the knowledge environment required to adopt EHRs.

Semantic Information and the Syntax of Propositional Attitude Verbs

ERIC Educational Resources Information Center

White, Aaron S.; Hacquard, Valentine; Lidz, Jeffrey

2018-01-01

Propositional attitude verbs, such as "think" and "want," have long held interest for both theoretical linguists and language acquisitionists because their syntactic, semantic, and pragmatic properties display complex interactions that have proven difficult to fully capture from either perspective. This paper explores the…

Fronto-temporal interactions are functionally relevant for semantic control in language processing.

PubMed

Wawrzyniak, Max; Hoffstaedter, Felix; Klingbeil, Julian; Stockert, Anika; Wrede, Katrin; Hartwigsen, Gesa; Eickhoff, Simon B; Classen, Joseph; Saur, Dorothee

2017-01-01

Semantic cognition, i.e. processing of meaning is based on semantic representations and their controlled retrieval. Semantic control has been shown to be implemented in a network that consists of left inferior frontal (IFG), and anterior and posterior middle temporal gyri (a/pMTG). We aimed to disrupt semantic control processes with continuous theta burst stimulation (cTBS) over left IFG and pMTG and to study whether behavioral effects are moderated by induced alterations in resting-state functional connectivity. To this end, we applied real cTBS over left IFG and left pMTG as well as sham stimulation on 20 healthy participants in a within-subject design. Stimulation was followed by resting-state functional magnetic resonance imaging and a semantic priming paradigm. Resting-state functional connectivity of regions of interest in left IFG, pMTG and aMTG revealed highly interconnected left-lateralized fronto-temporal networks representing the semantic system. We did not find any significant direct modulation of either task performance or resting-state functional connectivity by effective cTBS. However, after sham cTBS, functional connectivity between IFG and pMTG correlated with task performance under high semantic control demands in the semantic priming paradigm. These findings provide evidence for the functional relevance of interactions between IFG and pMTG for semantic control processes. This interaction was functionally less relevant after cTBS over aIFG which might be interpretable in terms of an indirect disruptive effect of cTBS.

Lexical-semantic processing in the semantic priming paradigm in aphasic patients.

PubMed

Salles, Jerusa Fumagalli de; Holderbaum, Candice Steffen; Parente, Maria Alice Mattos Pimenta; Mansur, Letícia Lessa; Ansaldo, Ana Inès

2012-09-01

There is evidence that the explicit lexical-semantic processing deficits which characterize aphasia may be observed in the absence of implicit semantic impairment. The aim of this article was to critically review the international literature on lexical-semantic processing in aphasia, as tested through the semantic priming paradigm. Specifically, this review focused on aphasia and lexical-semantic processing, the methodological strengths and weaknesses of the semantic paradigms used, and recent evidence from neuroimaging studies on lexical-semantic processing. Furthermore, evidence on dissociations between implicit and explicit lexical-semantic processing reported in the literature will be discussed and interpreted by referring to functional neuroimaging evidence from healthy populations. There is evidence that semantic priming effects can be found both in fluent and in non-fluent aphasias, and that these effects are related to an extensive network which includes the temporal lobe, the pre-frontal cortex, the left frontal gyrus, the left temporal gyrus and the cingulated cortex.

Morphometric information to reduce the semantic gap in the characterization of microscopic images of thyroid nodules.

PubMed

Macedo, Alessandra A; Pessotti, Hugo C; Almansa, Luciana F; Felipe, Joaquim C; Kimura, Edna T

2016-07-01

The analyses of several systems for medical-imaging processing typically support the extraction of image attributes, but do not comprise some information that characterizes images. For example, morphometry can be applied to find new information about the visual content of an image. The extension of information may result in knowledge. Subsequently, results of mappings can be applied to recognize exam patterns, thus improving the accuracy of image retrieval and allowing a better interpretation of exam results. Although successfully applied in breast lesion images, the morphometric approach is still poorly explored in thyroid lesions due to the high subjectivity thyroid examinations. This paper presents a theoretical-practical study, considering Computer Aided Diagnosis (CAD) and Morphometry, to reduce the semantic discontinuity between medical image features and human interpretation of image content. The proposed method aggregates the content of microscopic images characterized by morphometric information and other image attributes extracted by traditional object extraction algorithms. This method carries out segmentation, feature extraction, image labeling and classification. Morphometric analysis was included as an object extraction method in order to verify the improvement of its accuracy for automatic classification of microscopic images. To validate this proposal and verify the utility of morphometric information to characterize thyroid images, a CAD system was created to classify real thyroid image-exams into Papillary Cancer, Goiter and Non-Cancer. Results showed that morphometric information can improve the accuracy and precision of image retrieval and the interpretation of results in computer-aided diagnosis. For example, in the scenario where all the extractors are combined with the morphometric information, the CAD system had its best performance (70% of precision in Papillary cases). Results signalized a positive use of morphometric information from

Creating personalised clinical pathways by semantic interoperability with electronic health records.

PubMed

Wang, Hua-Qiong; Li, Jing-Song; Zhang, Yi-Fan; Suzuki, Muneou; Araki, Kenji

2013-06-01

There is a growing realisation that clinical pathways (CPs) are vital for improving the treatment quality of healthcare organisations. However, treatment personalisation is one of the main challenges when implementing CPs, and the inadequate dynamic adaptability restricts the practicality of CPs. The purpose of this study is to improve the practicality of CPs using semantic interoperability between knowledge-based CPs and semantic electronic health records (EHRs). Simple protocol and resource description framework query language is used to gather patient information from semantic EHRs. The gathered patient information is entered into the CP ontology represented by web ontology language. Then, after reasoning over rules described by semantic web rule language in the Jena semantic framework, we adjust the standardised CPs to meet different patients' practical needs. A CP for acute appendicitis is used as an example to illustrate how to achieve CP customisation based on the semantic interoperability between knowledge-based CPs and semantic EHRs. A personalised care plan is generated by comprehensively analysing the patient's personal allergy history and past medical history, which are stored in semantic EHRs. Additionally, by monitoring the patient's clinical information, an exception is recorded and handled during CP execution. According to execution results of the actual example, the solutions we present are shown to be technically feasible. This study contributes towards improving the clinical personalised practicality of standardised CPs. In addition, this study establishes the foundation for future work on the research and development of an independent CP system. Copyright © 2013 Elsevier B.V. All rights reserved.

Taxonomy, Ontology and Semantics at Johnson Space Center

NASA Technical Reports Server (NTRS)

Berndt, Sarah Ann

2011-01-01

At NASA Johnson Space Center (JSC), the Chief Knowledge Officer has been developing the JSC Taxonomy to capitalize on the accomplishments of yesterday while maintaining the flexibility needed for the evolving information environment of today. A clear vision and scope for the semantic system is integral to its success. The vision for the JSC Taxonomy is to connect information stovepipes to present a unified view for information and knowledge across the Center, across organizations, and across decades. Semantic search at JSC means seemless integration of disparate information sets into a single interface. Ever increasing use, interest, and organizational participation mark successful integration and provide the framework for future application.

Archetype-based semantic integration and standardization of clinical data.

PubMed

Moner, David; Maldonado, Jose A; Bosca, Diego; Fernandez, Jesualdo T; Angulo, Carlos; Crespo, Pere; Vivancos, Pedro J; Robles, Montserrat

2006-01-01

One of the basic needs for any healthcare professional is to be able to access to clinical information of patients in an understandable and normalized way. The lifelong clinical information of any person supported by electronic means configures his/her Electronic Health Record (EHR). This information is usually distributed among several independent and heterogeneous systems that may be syntactically or semantically incompatible. The Dual Model architecture has appeared as a new proposal for maintaining a homogeneous representation of the EHR with a clear separation between information and knowledge. Information is represented by a Reference Model which describes common data structures with minimal semantics. Knowledge is specified by archetypes, which are formal representations of clinical concepts built upon a particular Reference Model. This kind of architecture is originally thought for implantation of new clinical information systems, but archetypes can be also used for integrating data of existing and not normalized systems, adding at the same time a semantic meaning to the integrated data. In this paper we explain the possible use of a Dual Model approach for semantic integration and standardization of heterogeneous clinical data sources and present LinkEHR-Ed, a tool for developing archetypes as elements for integration purposes. LinkEHR-Ed has been designed to be easily used by the two main participants of the creation process of archetypes for clinical data integration: the Health domain expert and the Information Technologies domain expert.

Semantic Likelihood Models for Bayesian Inference in Human-Robot Interaction

NASA Astrophysics Data System (ADS)

Sweet, Nicholas

Autonomous systems, particularly unmanned aerial systems (UAS), remain limited in au- tonomous capabilities largely due to a poor understanding of their environment. Current sensors simply do not match human perceptive capabilities, impeding progress towards full autonomy. Recent work has shown the value of humans as sources of information within a human-robot team; in target applications, communicating human-generated 'soft data' to autonomous systems enables higher levels of autonomy through large, efficient information gains. This requires development of a 'human sensor model' that allows soft data fusion through Bayesian inference to update the probabilistic belief representations maintained by autonomous systems. Current human sensor models that capture linguistic inputs as semantic information are limited in their ability to generalize likelihood functions for semantic statements: they may be learned from dense data; they do not exploit the contextual information embedded within groundings; and they often limit human input to restrictive and simplistic interfaces. This work provides mechanisms to synthesize human sensor models from constraints based on easily attainable a priori knowledge, develops compression techniques to capture information-dense semantics, and investigates the problem of capturing and fusing semantic information contained within unstructured natural language. A robotic experimental testbed is also developed to validate the above contributions.

Toward semantic-based retrieval of visual information: a model-based approach

NASA Astrophysics Data System (ADS)

Park, Youngchoon; Golshani, Forouzan; Panchanathan, Sethuraman

2002-07-01

This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.

Model for Semantically Rich Point Cloud Data

NASA Astrophysics Data System (ADS)

Poux, F.; Neuville, R.; Hallot, P.; Billen, R.

2017-10-01

This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

Varieties of semantic 'access' deficit in Wernicke's aphasia and semantic aphasia.

PubMed

Thompson, Hannah E; Robson, Holly; Lambon Ralph, Matthew A; Jefferies, Elizabeth

2015-12-01

Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke's aphasia, associated with poor auditory-verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic 'access' deficit, as opposed to the 'storage' deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of 'access' impairment-related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke's aphasia). We used a case series design to compare patients with Wernicke's aphasia and those with semantic aphasia on Warrington's paradigmatic assessment of semantic 'access' deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic 'blocking' effects). Patients with Wernicke's aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability-one that mapped onto classical 'syndromes' and one that did not-predicted aspects of the semantic 'access' deficit. Both semantic aphasia and Wernicke's aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke's aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially 'beneficial' effects of stimulus repetition: cases with

Classification with an edge: Improving semantic image segmentation with boundary detection

NASA Astrophysics Data System (ADS)

Marmanis, D.; Schindler, K.; Wegner, J. D.; Galliani, S.; Datcu, M.; Stilla, U.

2018-01-01

We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art methods rely on DCNNs as their workhorse. A major reason for their success is that deep networks learn to accumulate contextual information over very large receptive fields. However, this success comes at a cost, since the associated loss of effective spatial resolution washes out high-frequency details and leads to blurry object boundaries. Here, we propose to counter this effect by combining semantic segmentation with semantically informed edge detection, thus making class boundaries explicit in the model. First, we construct a comparatively simple, memory-efficient model by adding boundary detection to the SEGNET encoder-decoder architecture. Second, we also include boundary detection in FCN-type models and set up a high-end classifier ensemble. We show that boundary detection significantly improves semantic segmentation with CNNs in an end-to-end training scheme. Our best model achieves >90% overall accuracy on the ISPRS Vaihingen benchmark.

A Joint Investigation of Semantic Facilitation and Semantic Interference in Continuous Naming

ERIC Educational Resources Information Center

Scaltritti, Michele; Peressotti, Francesca; Navarrete, Eduardo

2017-01-01

When speakers name multiple semantically related items, opposing effects can be found. Semantic facilitation is found when naming 2 semantically related items in a row. In contrast, semantic interference is found when speakers name semantically related items separated by 1 or more intervening unrelated items. This latter form of interference is…

Similar alterations in brain function for phonological and semantic processing to visual characters in Chinese dyslexia.

PubMed

Liu, Li; Wang, Wenjing; You, Wenping; Li, Yi; Awati, Neha; Zhao, Xu; Booth, James R; Peng, Danling

2012-07-01

Dyslexia in alphabetic languages has been extensively investigated and suggests a central deficit in orthography to phonology mapping in the left hemisphere. Compared to dyslexia in alphabetic languages, the central deficit for Chinese dyslexia is still unclear. Because of the logographic nature of Chinese characters, some have suggested that Chinese dyslexia should have larger deficits in the semantic system. To investigate this, Chinese children with reading disability (RD) were compared to typically developing (TD) children using functional magnetic resonance imaging (fMRI) on a rhyming judgment task and on a semantic association judgment task. RD children showed less activation for both tasks in right visual (BA18, 19) and left occipito-temporal cortex (BA 37), suggesting a deficit in visuo-orthographic processing. RD children also showed less activation for both tasks in left inferior frontal gyrus (BA44), which additionally showed significant correlations with activation of bilateral visuo-orthographic regions in the RD group, suggesting that the abnormalities in frontal cortex and in posterior visuo-orthographic regions may reflect a deficit in the connection between brain regions. Analyses failed to reveal larger differences between groups for the semantic compared to the rhyming task, suggesting that Chinese dyslexia is similarly impaired in the access to phonology and to semantics from the visual orthography. Copyright © 2012 Elsevier Ltd. All rights reserved.

Transcranial Direct Current Stimulation Effects on Semantic Processing in Healthy Individuals.

PubMed

Joyal, Marilyne; Fecteau, Shirley

2016-01-01

Semantic processing allows us to use conceptual knowledge about the world. It has been associated with a large distributed neural network that includes the frontal, temporal and parietal cortices. Recent studies using transcranial direct current stimulation (tDCS) also contributed at investigating semantic processing. The goal of this article was to review studies investigating semantic processing in healthy individuals with tDCS and discuss findings from these studies in line with neuroimaging results. Based on functional magnetic resonance imaging studies assessing semantic processing, we predicted that tDCS applied over the inferior frontal gyrus, middle temporal gyrus, and posterior parietal cortex will impact semantic processing. We conducted a search on Pubmed and selected 27 articles in which tDCS was used to modulate semantic processing in healthy subjects. We analysed each article according to these criteria: demographic information, experimental outcomes assessing semantic processing, study design, and effects of tDCS on semantic processes. From the 27 reviewed studies, 8 found main effects of stimulation. In addition to these 8 studies, 17 studies reported an interaction between stimulus types and stimulation conditions (e.g. incoherent functional, but not instrumental, actions were processed faster when anodal tDCS was applied over the posterior parietal cortex as compared to sham tDCS). Results suggest that regions in the frontal, temporal, and parietal cortices are involved in semantic processing. tDCS can modulate some aspects of semantic processing and provide information on the functional roles of brain regions involved in this cognitive process. Copyright © 2016 Elsevier Inc. All rights reserved.

A familiar pattern? Semantic memory contributes to the enhancement of visuo-spatial memories.

PubMed

Riby, Leigh M; Orme, Elizabeth

2013-03-01

In this study we quantify for the first time electrophysiological components associated with incorporating long-term semantic knowledge with visuo-spatial information using two variants of a traditional matrix patterns task. Results indicated that the matrix task with greater semantic content was associated with enhanced accuracy and RTs in a change-detection paradigm; this was also associated with increased P300 and N400 components as well as a sustained negative slow wave (NSW). In contrast, processing of the low semantic stimuli was associated with an increased N200 and a reduction in the P300. These findings suggest that semantic content can aid in reducing early visual processing of information and subsequent memory load by unitizing complex patterns into familiar forms. The N400/NSW may be associated with the requirements for maintaining visuo-spatial information about semantic forms such as orientation and relative location. Evidence for individual differences in semantic elaboration strategies used by participants is also discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Bridging the semantic gap in sports

NASA Astrophysics Data System (ADS)

Li, Baoxin; Errico, James; Pan, Hao; Sezan, M. Ibrahim

2003-01-01

One of the major challenges facing current media management systems and the related applications is the so-called "semantic gap" between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs. The framework is based on a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. An MPEG-7 compliant prototype browsing system has been implemented to demonstrate semantic retrieval and summarization of sports video.

Lexical and Sublexical Semantic Preview Benefits in Chinese Reading

ERIC Educational Resources Information Center

Yan, Ming; Zhou, Wei; Shu, Hua; Kliegl, Reinhold

2012-01-01

Semantic processing from parafoveal words is an elusive phenomenon in alphabetic languages, but it has been demonstrated only for a restricted set of noncompound Chinese characters. Using the gaze-contingent boundary paradigm, this experiment examined whether parafoveal lexical and sublexical semantic information was extracted from compound…

Generative Semantics.

ERIC Educational Resources Information Center

King, Margaret

The first section of this paper deals with the attempts within the framework of transformational grammar to make semantics a systematic part of linguistic description, and outlines the characteristics of the generative semantics position. The second section takes a critical look at generative semantics in its later manifestations, and makes a case…

Image segmentation via foreground and background semantic descriptors

NASA Astrophysics Data System (ADS)

Yuan, Ding; Qiang, Jingjing; Yin, Jihao

2017-09-01

In the field of image processing, it has been a challenging task to obtain a complete foreground that is not uniform in color or texture. Unlike other methods, which segment the image by only using low-level features, we present a segmentation framework, in which high-level visual features, such as semantic information, are used. First, the initial semantic labels were obtained by using the nonparametric method. Then, a subset of the training images, with a similar foreground to the input image, was selected. Consequently, the semantic labels could be further refined according to the subset. Finally, the input image was segmented by integrating the object affinity and refined semantic labels. State-of-the-art performance was achieved in experiments with the challenging MSRC 21 dataset.

Semantic Processing Impairment in Patients with Temporal Lobe Epilepsy

PubMed Central

Jaimes-Bautista, Amanda G.; Rodríguez-Camacho, Mario; Martínez-Juárez, Iris E.; Rodríguez-Agudelo, Yaneth

2015-01-01

The impairment in episodic memory system is the best-known cognitive deficit in patients with temporal lobe epilepsy (TLE). Recent studies have shown evidence of semantic disorders, but they have been less studied than episodic memory. The semantic dysfunction in TLE has various cognitive manifestations, such as the presence of language disorders characterized by defects in naming, verbal fluency, or remote semantic information retrieval, which affects the ability of patients to interact with their surroundings. This paper is a review of recent research about the consequences of TLE on semantic processing, considering neuropsychological, electrophysiological, and neuroimaging findings, as well as the functional role of the hippocampus in semantic processing. The evidence from these studies shows disturbance of semantic memory in patients with TLE and supports the theory of declarative memory of the hippocampus. Functional neuroimaging studies show an inefficient compensatory functional reorganization of semantic networks and electrophysiological studies show a lack of N400 effect that could indicate that the deficit in semantic processing in patients with TLE could be due to a failure in the mechanisms of automatic access to lexicon. PMID:26257956

Individual differences in white matter microstructure predict semantic control.

PubMed

Nugiel, Tehila; Alm, Kylie H; Olson, Ingrid R

2016-12-01

In everyday conversation, we make many rapid choices between competing concepts and words in order to convey our intent. This process is termed semantic control, and it is thought to rely on information transmission between a distributed semantic store in the temporal lobes and a more discrete region, optimized for retrieval and selection, in the left inferior frontal gyrus. Here, we used diffusion tensor imaging in a group of neurologically normal young adults to investigate the relationship between semantic control and white matter tracts that have been implicated in semantic memory retrieval. Participants completed a verb generation task that taps semantic control (Snyder & Munakata, 2008; Snyder et al., 2010) and underwent a diffusion imaging scan. Deterministic tractography was performed to compute indices representing the microstructural properties of the inferior fronto-occipital fasciculus (IFOF), the uncinate fasciculus (UF), and the inferior longitudinal fasciculus (ILF). Microstructural measures of the UF failed to predict semantic control performance. However, there was a significant relationship between microstructure of the left IFOF and ILF and individual differences in semantic control. Our findings support the view put forth by Duffau (2013) that the IFOF is a key structural pathway in semantic retrieval.

Functional changes in the cortical semantic network in amnestic mild cognitive impairment.

PubMed

Pineault, Jessica; Jolicoeur, Pierre; Grimault, Stephan; Bermudez, Patrick; Brambati, Simona Maria; Lacombe, Jacinthe; Villalpando, Juan Manuel; Kergoat, Marie-Jeanne; Joubert, Sven

2018-05-01

Semantic memory impairment has been documented in individuals with amnestic Mild cognitive impairment (aMCI), who are at risk of developing Alzheimer's disease (AD), yet little is known about the neural basis of this breakdown. The aim of this study was to investigate the brain mechanisms associated with semantic performance in aMCI patients. A group of aMCI patients and a group of healthy controls carried out a semantic categorization task while their brain activity was recorded using magnetoencephalography (MEG). During the task, participants were shown famous faces and had to determine whether each famous person matched a given occupation. The main hypotheses were that (a) semantic processing should be compromised for aMCI patients, and (b) these deficits should be associated with cortical dysfunctions within specific areas of the semantic network. Behavioral results showed that aMCI participants were significantly slower and less accurate than controls at the semantic task. Additionally, relative to controls, a significant pattern of hyperactivation was found in the aMCI group within specific regions of the extended semantic network, including the right anterior temporal lobe (ATL) and fusiform gyrus. Abnormal functional activation within key areas of the semantic network suggests that it is compromised early in the disease process. Moreover, this pattern of right ATL and fusiform gyrus hyperactivation was positively associated with gray matter integrity in specific areas, but was not associated with any pattern of atrophy, suggesting that this pattern of hyperactivation may precede structural alteration of the semantic network in aMCI. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Cross-language parafoveal semantic processing: Evidence from Korean-Chinese bilinguals.

PubMed

Wang, Aiping; Yeon, Junmo; Zhou, Wei; Shu, Hua; Yan, Ming

2016-02-01

In the present study, we aimed at testing cross-language cognate and semantic preview effects. We tested how native Korean readers who learned Chinese as a second language make use of the parafoveal information during the reading of Chinese sentences. There were 3 types of Korean preview words: cognate translations of the Chinese target words, semantically related noncognate words, and unrelated words. Together with a highly significant cognate preview effect, more critically, we also observed reliable facilitation in processing of the target word from the semantically related previews in all fixation measures. Results from the present study provide first evidence for semantic processing from parafoveally presented Korean words and for cross-language parafoveal semantic processing.

iPad: Semantic annotation and markup of radiological images.

PubMed

Rubin, Daniel L; Rodriguez, Cesar; Shah, Priyanka; Beaulieu, Chris

2008-11-06

Radiological images contain a wealth of information,such as anatomy and pathology, which is often not explicit and computationally accessible. Information schemes are being developed to describe the semantic content of images, but such schemes can be unwieldy to operationalize because there are few tools to enable users to capture structured information easily as part of the routine research workflow. We have created iPad, an open source tool enabling researchers and clinicians to create semantic annotations on radiological images. iPad hides the complexity of the underlying image annotation information model from users, permitting them to describe images and image regions using a graphical interface that maps their descriptions to structured ontologies semi-automatically. Image annotations are saved in a variety of formats,enabling interoperability among medical records systems, image archives in hospitals, and the Semantic Web. Tools such as iPad can help reduce the burden of collecting structured information from images, and it could ultimately enable researchers and physicians to exploit images on a very large scale and glean the biological and physiological significance of image content.

EXACT2: the semantics of biomedical protocols

PubMed Central

2014-01-01

Background The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. Methods We have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously 'unseen' (not used for the construction of EXACT2) protocols. Results The paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed. Conclusions The EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically

Distinct behavioural profiles in frontotemporal dementia and semantic dementia

PubMed Central

Snowden, J; Bathgate, D; Varma, A; Blackshaw, A; Gibbons, Z; Neary, D

2001-01-01

OBJECTIVE—To test predictions that frontotemporal dementia and semantic dementia give rise to distinct patterns of behavioural change.
METHODS—An informant based semistructured behavioural interview, covering the domains of basic and social emotions, social and personal behaviour, sensory behaviour, eating and oral behaviour, repetitive behaviours, rituals, and compulsions, was administered to carers of 41 patients with semantic dementia and with apathetic (FTD-A) and disinhibited (FTD-D) forms of frontotemporal dementia.
RESULTS—Consistent with prediction, emotional changes differentiated FTD from semantic dementia. Whereas lack of emotional response was pervasive in FTD, it was more selective in semantic dementia, affecting particularly the capacity to show fear. Social avoidance occurred more often in FTD and social seeking in semantic dementia. Patients with FTD showed reduced response to pain, whereas patients with semantic dementia more often showed exaggerated reactions to sensory stimuli. Gluttony and indiscriminate eating were characteristic of FTD, whereas patients with semantic dementia were more likely to exhibit food fads. Hyperorality, involving inedible objects, was unrelated to gluttony, indicating different underlying mechanisms. Repetitive behaviours were common in both FTD and semantic dementia, but had a more compulsive quality in semantic dementia. Behavioural differences were greater between semantic dementia and FTD-A than FTD-D. A logistic regression analysis indicated that emotional and repetitive, compulsive behaviours discriminated FTD from semantic dementia with 97% accuracy.
CONCLUSION—The findings confirm predictions regarding behavioural differences in frontotemporal and semantic dementia and point to differential roles of the frontal and temporal lobes in affect, social functioning, eating, and compulsive behaviour.

 PMID:11181853

Towards Automatic Semantic Labelling of 3D City Models

NASA Astrophysics Data System (ADS)

Rook, M.; Biljecki, F.; Diakité, A. A.

2016-10-01

The lack of semantic information in many 3D city models is a considerable limiting factor in their use, as a lot of applications rely on semantics. Such information is not always available, since it is not collected at all times, it might be lost due to data transformation, or its lack may be caused by non-interoperability in data integration from other sources. This research is a first step in creating an automatic workflow that semantically labels plain 3D city model represented by a soup of polygons, with semantic and thematic information, as defined in the CityGML standard. The first step involves the reconstruction of the topology, which is used in a region growing algorithm that clusters upward facing adjacent triangles. Heuristic rules, embedded in a decision tree, are used to compute a likeliness score for these regions that either represent the ground (terrain) or a RoofSurface. Regions with a high likeliness score, to one of the two classes, are used to create a decision space, which is used in a support vector machine (SVM). Next, topological relations are utilised to select seeds that function as a start in a region growing algorithm, to create regions of triangles of other semantic classes. The topological relationships of the regions are used in the aggregation of the thematic building features. Finally, the level of detail is detected to generate the correct output in CityGML. The results show an accuracy between 85 % and 99 % in the automatic semantic labelling on four different test datasets. The paper is concluded by indicating problems and difficulties implying the next steps in the research.

A user-centred evaluation framework for the Sealife semantic web browsers.

PubMed

Oliver, Helen; Diallo, Gayo; de Quincey, Ed; Alexopoulou, Dimitra; Habermann, Bianca; Kostkova, Patty; Schroeder, Michael; Jupp, Simon; Khelif, Khaled; Stevens, Robert; Jawaheer, Gawesh; Madle, Gemma

2009-10-01

Semantically-enriched browsing has enhanced the browsing experience by providing contextualized dynamically generated Web content, and quicker access to searched-for information. However, adoption of Semantic Web technologies is limited and user perception from the non-IT domain sceptical. Furthermore, little attention has been given to evaluating semantic browsers with real users to demonstrate the enhancements and obtain valuable feedback. The Sealife project investigates semantic browsing and its application to the life science domain. Sealife's main objective is to develop the notion of context-based information integration by extending three existing Semantic Web browsers (SWBs) to link the existing Web to the eScience infrastructure. This paper describes a user-centred evaluation framework that was developed to evaluate the Sealife SWBs that elicited feedback on users' perceptions on ease of use and information findability. Three sources of data: i) web server logs; ii) user questionnaires; and iii) semi-structured interviews were analysed and comparisons made between each browser and a control system. It was found that the evaluation framework used successfully elicited users' perceptions of the three distinct SWBs. The results indicate that the browser with the most mature and polished interface was rated higher for usability, and semantic links were used by the users of all three browsers. Confirmation or contradiction of our original hypotheses with relation to SWBs is detailed along with observations of implementation issues.

Trust estimation of the semantic web using semantic web clustering

NASA Astrophysics Data System (ADS)

Shirgahi, Hossein; Mohsenzadeh, Mehran; Haj Seyyed Javadi, Hamid

2017-05-01

Development of semantic web and social network is undeniable in the Internet world these days. Widespread nature of semantic web has been very challenging to assess the trust in this field. In recent years, extensive researches have been done to estimate the trust of semantic web. Since trust of semantic web is a multidimensional problem, in this paper, we used parameters of social network authority, the value of pages links authority and semantic authority to assess the trust. Due to the large space of semantic network, we considered the problem scope to the clusters of semantic subnetworks and obtained the trust of each cluster elements as local and calculated the trust of outside resources according to their local trusts and trust of clusters to each other. According to the experimental result, the proposed method shows more than 79% Fscore that is about 11.9% in average more than Eigen, Tidal and centralised trust methods. Mean of error in this proposed method is 12.936, that is 9.75% in average less than Eigen and Tidal trust methods.

Shared Semantics and the Use of Organizational Memories for E-Mail Communications.

ERIC Educational Resources Information Center

Schwartz, David G.

1998-01-01

Examines the use of shared semantics information to link concepts in an organizational memory to e-mail communications. Presents a framework for determining shared semantics based on organizational and personal user profiles. Illustrates how shared semantics are used by the HyperMail system to help link organizational memories (OM) content to…

Is semantic fluency differentially impaired in schizophrenic patients with delusions?

PubMed

Rossell, S L; Rabe-Hesketh, S S; Shapleske, J S; David, A S

1999-10-01

The study of cognitive deficits in schizophrenia has recently focused upon semantics: the study of meaning. Delusions are a plausible manifestation of abnormal semantics because by definition they involve changes in personal meaning and belief. A symptom-based approach was used to investigate semantic and phonological fluency in a group of schizophrenic patients subdivided into those with delusions and those with no current delusions. The results demonstrated that deluded patients only were differentially impaired on a test of semantic fluency in comparison to phonological fluency. All subjects showed the same decline in performance over the time course of both tests indicating that retrieval speed in schizophrenia is no different from that of normal controls. Further analysis of word associations in two semantic categories (animals and body parts), revealed that deluded subjects have a more idiosyncratic organisation for animals. The findings of reduced semantic fluency production and poor logical word associations may represent a disorganised storage of semantic information in deluded patients, which in turn affects efficient access.

Designing learning management system interoperability in semantic web

NASA Astrophysics Data System (ADS)

Anistyasari, Y.; Sarno, R.; Rochmawati, N.

2018-01-01

The extensive adoption of learning management system (LMS) has set the focus on the interoperability requirement. Interoperability is the ability of different computer systems, applications or services to communicate, share and exchange data, information, and knowledge in a precise, effective and consistent way. Semantic web technology and the use of ontologies are able to provide the required computational semantics and interoperability for the automation of tasks in LMS. The purpose of this study is to design learning management system interoperability in the semantic web which currently has not been investigated deeply. Moodle is utilized to design the interoperability. Several database tables of Moodle are enhanced and some features are added. The semantic web interoperability is provided by exploited ontology in content materials. The ontology is further utilized as a searching tool to match user’s queries and available courses. It is concluded that LMS interoperability in Semantic Web is possible to be performed.

A Collection of Features for Semantic Graphs

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

Eliassi-Rad, T; Fodor, I K; Gallagher, B

2007-05-02

Semantic graphs are commonly used to represent data from one or more data sources. Such graphs extend traditional graphs by imposing types on both nodes and links. This type information defines permissible links among specified nodes and can be represented as a graph commonly referred to as an ontology or schema graph. Figure 1 depicts an ontology graph for data from National Association of Securities Dealers. Each node type and link type may also have a list of attributes. To capture the increased complexity of semantic graphs, concepts derived for standard graphs have to be extended. This document explains brieflymore » features commonly used to characterize graphs, and their extensions to semantic graphs. This document is divided into two sections. Section 2 contains the feature descriptions for static graphs. Section 3 extends the features for semantic graphs that vary over time.« less

Right anterior temporal lobe dysfunction underlies theory of mind impairments in semantic dementia.

PubMed

Irish, Muireann; Hodges, John R; Piguet, Olivier

2014-04-01

Semantic dementia is a progressive neurodegenerative disorder characterized by the amodal and profound loss of semantic knowledge attributable to the degeneration of the left anterior temporal lobe. Although traditionally conceptualized as a language disorder, patients with semantic dementia display significant alterations in behaviour and socioemotional functioning. Recent evidence points to an impaired capacity for theory of mind in predominantly left-lateralized cases of semantic dementia; however, it remains unclear to what extent semantic impairments contribute to these deficits. Further the neuroanatomical signature of such disturbance remains unknown. Here, we sought to determine the neural correlates of theory of mind performance in patients with left predominant semantic dementia (n=11), in contrast with disease-matched cases with behavioural-variant frontotemporal dementia (n=10) and Alzheimer's disease (n=10), and healthy older individuals (n=14) as control participants. Participants completed a simple cartoons task, in which they were required to describe physical and theory of mind scenarios. Irrespective of subscale, patients with semantic dementia exhibited marked impairments relative to control subjects; however, only theory of mind deficits persisted when we covaried for semantic comprehension. Voxel-based morphometry analyses revealed that atrophy in right anterior temporal lobe structures, including the right temporal fusiform cortex, right inferior temporal gyrus, bilateral temporal poles and amygdalae, correlated significantly with theory of mind impairments in the semantic dementia group. Our results point to the marked disruption of cognitive functions beyond the language domain in semantic dementia, not exclusively attributable to semantic processing impairments. The significant involvement of right anterior temporal structures suggests that with disease evolution, the encroachment of pathology into the contralateral hemisphere heralds the

Language and culture modulate online semantic processing.

PubMed

Ellis, Ceri; Kuipers, Jan R; Thierry, Guillaume; Lovett, Victoria; Turnbull, Oliver; Jones, Manon W

2015-10-01

Language has been shown to influence non-linguistic cognitive operations such as colour perception, object categorization and motion event perception. Here, we show that language also modulates higher level processing, such as semantic knowledge. Using event-related brain potentials, we show that highly fluent Welsh-English bilinguals require significantly less processing effort when reading sentences in Welsh which contain factually correct information about Wales, than when reading sentences containing the same information presented in English. Crucially, culturally irrelevant information was processed similarly in both Welsh and English. Our findings show that even in highly proficient bilinguals, language interacts with factors associated with personal identity, such as culture, to modulate online semantic processing. © The Author (2015). Published by Oxford University Press.

The Role of Shape in Semantic Memory Organization of Objects: An Experimental Study Using PI-Release.

PubMed

van Weelden, Lisanne; Schilperoord, Joost; Swerts, Marc; Pecher, Diane

2015-01-01

Visual information contributes fundamentally to the process of object categorization. The present study investigated whether the degree of activation of visual information in this process is dependent on the contextual relevance of this information. We used the Proactive Interference (PI-release) paradigm. In four experiments, we manipulated the information by which objects could be categorized and subsequently be retrieved from memory. The pattern of PI-release showed that if objects could be stored and retrieved both by (non-perceptual) semantic and (perceptual) shape information, then shape information was overruled by semantic information. If, however, semantic information could not be (satisfactorily) used to store and retrieve objects, then objects were stored in memory in terms of their shape. The latter effect was found to be strongest for objects from identical semantic categories.

Predication-based semantic indexing: permutations as a means to encode predications in semantic space.

PubMed

Cohen, Trevor; Schvaneveldt, Roger W; Rindflesch, Thomas C

2009-11-14

Corpus-derived distributional models of semantic distance between terms have proved useful in a number of applications. For both theoretical and practical reasons, it is desirable to extend these models to encode discrete concepts and the ways in which they are related to one another. In this paper, we present a novel vector space model that encodes semantic predications derived from MEDLINE by the SemRep system into a compact spatial representation. The associations captured by this method are of a different and complementary nature to those derived by traditional vector space models, and the encoding of predication types presents new possibilities for knowledge discovery and information retrieval.

Spicy Adjectives and Nominal Donkeys: Capturing Semantic Deviance Using Compositionality in Distributional Spaces.

PubMed

Vecchi, Eva M; Marelli, Marco; Zamparelli, Roberto; Baroni, Marco

2017-01-01

Sophisticated senator and legislative onion. Whether or not you have ever heard of these things, we all have some intuition that one of them makes much less sense than the other. In this paper, we introduce a large dataset of human judgments about novel adjective-noun phrases. We use these data to test an approach to semantic deviance based on phrase representations derived with compositional distributional semantic methods, that is, methods that derive word meanings from contextual information, and approximate phrase meanings by combining word meanings. We present several simple measures extracted from distributional representations of words and phrases, and we show that they have a significant impact on predicting the acceptability of novel adjective-noun phrases even when a number of alternative measures classically employed in studies of compound processing and bigram plausibility are taken into account. Our results show that the extent to which an attributive adjective alters the distributional representation of the noun is the most significant factor in modeling the distinction between acceptable and deviant phrases. Our study extends current applications of compositional distributional semantic methods to linguistically and cognitively interesting problems, and it offers a new, quantitatively precise approach to the challenge of predicting when humans will find novel linguistic expressions acceptable and when they will not. Copyright © 2016 Cognitive Science Society, Inc.

Semantic Analysis of Email Using Domain Ontologies and WordNet

NASA Technical Reports Server (NTRS)

Berrios, Daniel C.; Keller, Richard M.

2005-01-01

The problem of capturing and accessing knowledge in paper form has been supplanted by a problem of providing structure to vast amounts of electronic information. Systems that can construct semantic links for natural language documents like email messages automatically will be a crucial element of semantic email tools. We have designed an information extraction process that can leverage the knowledge already contained in an existing semantic web, recognizing references in email to existing nodes in a network of ontology instances by using linguistic knowledge and knowledge of the structure of the semantic web. We developed a heuristic score that uses several forms of evidence to detect references in email to existing nodes in the Semanticorganizer repository's network. While these scores cannot directly support automated probabilistic inference, they can be used to rank nodes by relevance and link those deemed most relevant to email messages.

Interactions between statistical and semantic information in infant language development

PubMed Central

Lany, Jill; Saffran, Jenny R.

2013-01-01

Infants can use statistical regularities to form rudimentary word categories (e.g. noun, verb), and to learn the meanings common to words from those categories. Using an artificial language methodology, we probed the mechanisms by which two types of statistical cues (distributional and phonological regularities) affect word learning. Because linking distributional cues vs. phonological information to semantics make different computational demands on learners, we also tested whether their use is related to language proficiency. We found that 22-month-old infants with smaller vocabularies generalized using phonological cues; however, infants with larger vocabularies showed the opposite pattern of results, generalizing based on distributional cues. These findings suggest that both phonological and distributional cues marking word categories promote early word learning. Moreover, while correlations between these cues are important to forming word categories, we found infants’ weighting of these cues in subsequent word-learning tasks changes over the course of early language development. PMID:21884336

[Evaluation of temporality semantic knowledge in normal aging and in mild and moderate stages of Alzheimer's disease].

PubMed

Rivasseau Jonveaux, T; Batt, M; Empereur, F; Braun, M; Trognon, A

2015-04-01

Episodic and semantic processes are involved in temporality used in daily life. Episodic memory permits one to place an event on the time axis, while semantic memory makes us aware of the time segmentation and its symbolic representation. Memory of the knowledge connected to the passing of time is materialized on the calendar and can be seen symbolically on the dial of a clock. In AD, semantic memory processes are preserved longer than processes related to episodic memory. We wonder whether the specific field of knowledge about time is altered during AD. We validated a specific evaluation with a control group (354 healthy subjects). Then we applied this battery to assess AD patients to appreciate the feasibility of this tool for this population. We then compared 22 AD patients with a control group matched for age, sex and educational level. Our clinical scale of temporal semantic knowledge consists of four parts: (a) hour reading with a.m. and p.m. hours; (b) using a clock: 12 clock faces with the hour numbers already placed: the patient draws hour and minute hands for various hours; (c) temporal segmentation: exploration of the knowledge on daytime scale and of the calendar; (d) time duration estimation: calculate how long the interview has lasted after indicating the time of its beginning and its end, then the time between 10.40 to 12.00. While age and educational level had an influence on all the scores, in the two groups control and patients, gender did not. Temporal segmentation, independent of the cultural level, revealed the best acquired knowledge in our control population. All the scores differentiated patients from control subjects. The temporal semantic knowledge correlated with the AD severity seemed to be correlated with the attention, verbal comprehension, and some components of executive functions, but was not related to the clock drawing test result. Depression did not have any influence on this scale in our AD group. The temporal semantic knowledge

Type-specific proactive interference in patients with semantic and phonological STM deficits.

PubMed

Harris, Lara; Olson, Andrew; Humphreys, Glyn

2014-01-01

Prior neuropsychological evidence suggests that semantic and phonological components of short-term memory (STM) are functionally and neurologically distinct. The current paper examines proactive interference (PI) from semantic and phonological information in two STM-impaired patients, DS (semantic STM deficit) and AK (phonological STM deficit). In Experiment 1 probe recognition tasks with open and closed sets of stimuli were used. Phonological PI was assessed using nonword items, and semantic and phonological PI was assessed using words. In Experiment 2 phonological and semantic PI was elicited by an item recognition probe test with stimuli that bore phonological and semantic relations to the probes. The data suggested heightened phonological PI for the semantic STM patient, and exaggerated effects of semantic PI in the phonological STM case. The findings are consistent with an account of extremely rapid decay of activated type-specific representations in cases of severely impaired phonological and semantic STM.

Remote semantic memory for public figures in HIV infection, alcoholism, and their comorbidity.

PubMed

Fama, Rosemary; Rosenbloom, Margaret J; Sassoon, Stephanie A; Thompson, Megan A; Pfefferbaum, Adolf; Sullivan, Edith V

2011-02-01

Impairments in component processes of working and episodic memory mark both HIV infection and chronic alcoholism, with compounded deficits often observed in individuals comorbid for these conditions. Remote semantic memory processes, however, have only seldom been studied in these diagnostic groups. Examination of remote semantic memory could provide insight into the underlying processes associated with storage and retrieval of learned information over extended time periods while elucidating spared and impaired cognitive functions in these clinical groups. We examined component processes of remote semantic memory in HIV infection and chronic alcoholism in 4 subject groups (HIV, ALC, HIV + ALC, and age-matched healthy adults) using a modified version of the Presidents Test. Free recall, recognition, and sequencing of presidential candidates and election dates were assessed. In addition, component processes of working, episodic, and semantic memory were assessed with ancillary cognitive tests. The comorbid group (HIV + ALC) was significantly impaired on sequencing of remote semantic information compared with age-matched healthy adults. Free recall of remote semantic information was also modestly impaired in the HIV + ALC group, but normal performance for recognition of this information was observed. Few differences were observed between the single diagnosis groups (HIV, ALC) and healthy adults, although examination of the component processes underlying remote semantic memory scores elicited differences between the HIV and ALC groups. Selective remote memory processes were related to lifetime alcohol consumption in the ALC group and to viral load and depression level in the HIV group. Hepatitis C diagnosis was associated with lower remote semantic memory scores in all 3 clinical groups. Education level did not account for group differences reported. This study provides behavioral support for the existence of adverse effects associated with the comorbidity of HIV

Semantic interoperability--HL7 Version 3 compared to advanced architecture standards.

PubMed

Blobel, B G M E; Engel, K; Pharow, P

2006-01-01

To meet the challenge for high quality and efficient care, highly specialized and distributed healthcare establishments have to communicate and co-operate in a semantically interoperable way. Information and communication technology must be open, flexible, scalable, knowledge-based and service-oriented as well as secure and safe. For enabling semantic interoperability, a unified process for defining and implementing the architecture, i.e. structure and functions of the cooperating systems' components, as well as the approach for knowledge representation, i.e. the used information and its interpretation, algorithms, etc. have to be defined in a harmonized way. Deploying the Generic Component Model, systems and their components, underlying concepts and applied constraints must be formally modeled, strictly separating platform-independent from platform-specific models. As HL7 Version 3 claims to represent the most successful standard for semantic interoperability, HL7 has been analyzed regarding the requirements for model-driven, service-oriented design of semantic interoperable information systems, thereby moving from a communication to an architecture paradigm. The approach is compared with advanced architectural approaches for information systems such as OMG's CORBA 3 or EHR systems such as GEHR/openEHR and CEN EN 13606 Electronic Health Record Communication. HL7 Version 3 is maturing towards an architectural approach for semantic interoperability. Despite current differences, there is a close collaboration between the teams involved guaranteeing a convergence between competing approaches.

Effects of semantic relatedness on recall of stimuli preceding emotional oddballs.

PubMed

Smith, Ryan M; Beversdorf, David Q

2008-07-01

Semantic and episodic memory networks function as highly interconnected systems, both relying on the hippocampal/medial temporal lobe complex (HC/MTL). Episodic memory encoding triggers the retrieval of semantic information, serving to incorporate contextual relationships between the newly acquired memory and existing semantic representations. While emotional material augments episodic memory encoding at the time of stimulus presentation, interactions between emotion and semantic memory that contribute to subsequent episodic recall are not well understood. Using a modified oddball task, we examined the modulatory effects of negative emotion on semantic interactions with episodic memory by measuring the free-recall of serially presented neutral or negative words varying in semantic relatedness. We found increased free-recall for words related to and preceding emotionally negative oddballs, suggesting that negative emotion can indirectly facilitate episodic free-recall by enhancing semantic contributions during encoding. Our findings demonstrate the ability of emotion and semantic memory to interact to mutually enhance free-recall.

Natural speech reveals the semantic maps that tile human cerebral cortex

PubMed Central

Huth, Alexander G.; de Heer, Wendy A.; Griffiths, Thomas L.; Theunissen, Frédéric E.; Gallant, Jack L.

2016-01-01

The meaning of language is represented in regions of the cerebral cortex collectively known as the “semantic system”. However, little of the semantic system has been mapped comprehensively, and the semantic selectivity of most regions is unknown. Here we systematically map semantic selectivity across the cortex using voxel-wise modeling of fMRI data collected while subjects listened to hours of narrative stories. We show that the semantic system is organized into intricate patterns that appear consistent across individuals. We then use a novel generative model to create a detailed semantic atlas. Our results suggest that most areas within the semantic system represent information about specific semantic domains, or groups of related concepts, and our atlas shows which domains are represented in each area. This study demonstrates that data-driven methods—commonplace in studies of human neuroanatomy and functional connectivity—provide a powerful and efficient means for mapping functional representations in the brain. PMID:27121839

"Pre-Semantic" Cognition Revisited: Critical Differences between Semantic Aphasia and Semantic Dementia

ERIC Educational Resources Information Center

Jefferies, Elizabeth; Rogers, Timothy T.; Hopper, Samantha; Lambon Ralph, Matthew A.

2010-01-01

Patients with semantic dementia show a specific pattern of impairment on both verbal and non-verbal "pre-semantic" tasks, e.g., reading aloud, past tense generation, spelling to dictation, lexical decision, object decision, colour decision and delayed picture copying. All seven tasks are characterised by poorer performance for items that are…

The methodology of semantic analysis for extracting physical effects

NASA Astrophysics Data System (ADS)

Fomenkova, M. A.; Kamaev, V. A.; Korobkin, D. M.; Fomenkov, S. A.

2017-01-01

The paper represents new methodology of semantic analysis for physical effects extracting. This methodology is based on the Tuzov ontology that formally describes the Russian language. In this paper, semantic patterns were described to extract structural physical information in the form of physical effects. A new algorithm of text analysis was described.

Semantic Desktop

NASA Astrophysics Data System (ADS)

Sauermann, Leo; Kiesel, Malte; Schumacher, Kinga; Bernardi, Ansgar

In diesem Beitrag wird gezeigt, wie der Arbeitsplatz der Zukunft aussehen könnte und wo das Semantic Web neue Möglichkeiten eröffnet. Dazu werden Ansätze aus dem Bereich Semantic Web, Knowledge Representation, Desktop-Anwendungen und Visualisierung vorgestellt, die es uns ermöglichen, die bestehenden Daten eines Benutzers neu zu interpretieren und zu verwenden. Dabei bringt die Kombination von Semantic Web und Desktop Computern besondere Vorteile - ein Paradigma, das unter dem Titel Semantic Desktop bekannt ist. Die beschriebenen Möglichkeiten der Applikationsintegration sind aber nicht auf den Desktop beschränkt, sondern können genauso in Web-Anwendungen Verwendung finden.

Somatotopic Semantic Priming and Prediction in the Motor System

PubMed Central

Grisoni, Luigi; Dreyer, Felix R.; Pulvermüller, Friedemann

2016-01-01

The recognition of action-related sounds and words activates motor regions, reflecting the semantic grounding of these symbols in action information; in addition, motor cortex exerts causal influences on sound perception and language comprehension. However, proponents of classic symbolic theories still dispute the role of modality-preferential systems such as the motor cortex in the semantic processing of meaningful stimuli. To clarify whether the motor system carries semantic processes, we investigated neurophysiological indexes of semantic relationships between action-related sounds and words. Event-related potentials revealed that action-related words produced significantly larger stimulus-evoked (Mismatch Negativity-like) and predictive brain responses (Readiness Potentials) when presented in body-part-incongruent sound contexts (e.g., “kiss” in footstep sound context; “kick” in whistle context) than in body-part-congruent contexts, a pattern reminiscent of neurophysiological correlates of semantic priming. Cortical generators of the semantic relatedness effect were localized in areas traditionally associated with semantic memory, including left inferior frontal cortex and temporal pole, and, crucially, in motor areas, where body-part congruency of action sound–word relationships was indexed by a somatotopic pattern of activation. As our results show neurophysiological manifestations of action-semantic priming in the motor cortex, they prove semantic processing in the motor system and thus in a modality-preferential system of the human brain. PMID:26908635

Occipital cortical thickness in very low birth weight born adolescents predicts altered neural specialization of visual semantic category related neural networks.

PubMed

Klaver, Peter; Latal, Beatrice; Martin, Ernst

2015-01-01

Very low birth weight (VLBW) premature born infants have a high risk to develop visual perceptual and learning deficits as well as widespread functional and structural brain abnormalities during infancy and childhood. Whether and how prematurity alters neural specialization within visual neural networks is still unknown. We used functional and structural brain imaging to examine the visual semantic system of VLBW born (<1250 g, gestational age 25-32 weeks) adolescents (13-15 years, n = 11, 3 males) and matched term born control participants (13-15 years, n = 11, 3 males). Neurocognitive assessment revealed no group differences except for lower scores on an adaptive visuomotor integration test. All adolescents were scanned while viewing pictures of animals and tools and scrambled versions of these pictures. Both groups demonstrated animal and tool category related neural networks. Term born adolescents showed tool category related neural activity, i.e. tool pictures elicited more activity than animal pictures, in temporal and parietal brain areas. Animal category related activity was found in the occipital, temporal and frontal cortex. VLBW born adolescents showed reduced tool category related activity in the dorsal visual stream compared with controls, specifically the left anterior intraparietal sulcus, and enhanced animal category related activity in the left middle occipital gyrus and right lingual gyrus. Lower birth weight of VLBW adolescents correlated with larger thickness of the pericalcarine gyrus in the occipital cortex and smaller surface area of the superior temporal gyrus in the lateral temporal cortex. Moreover, larger thickness of the pericalcarine gyrus and smaller surface area of the superior temporal gyrus correlated with reduced tool category related activity in the parietal cortex. Together, our data suggest that very low birth weight predicts alterations of higher order visual semantic networks, particularly in the dorsal stream. The differences

Eye Movements to Pictures Reveal Transient Semantic Activation during Spoken Word Recognition

ERIC Educational Resources Information Center

Yee, Eiling; Sedivy, Julie C.

2006-01-01

Two experiments explore the activation of semantic information during spoken word recognition. Experiment 1 shows that as the name of an object unfolds (e.g., lock), eye movements are drawn to pictorial representations of both the named object and semantically related objects (e.g., key). Experiment 2 shows that objects semantically related to an…

Architecture for WSN Nodes Integration in Context Aware Systems Using Semantic Messages

NASA Astrophysics Data System (ADS)

Larizgoitia, Iker; Muguira, Leire; Vazquez, Juan Ignacio

Wireless sensor networks (WSN) are becoming extremely popular in the development of context aware systems. Traditionally WSN have been focused on capturing data, which was later analyzed and interpreted in a server with more computational power. In this kind of scenario the problem of representing the sensor information needs to be addressed. Every node in the network might have different sensors attached; therefore their correspondent packet structures will be different. The server has to be aware of the meaning of every single structure and data in order to be able to interpret them. Multiple sensors, multiple nodes, multiple packet structures (and not following a standard format) is neither scalable nor interoperable. Context aware systems have solved this problem with the use of semantic technologies. They provide a common framework to achieve a standard definition of any domain. Nevertheless, these representations are computationally expensive, so a WSN cannot afford them. The work presented in this paper tries to bridge the gap between the sensor information and its semantic representation, by defining a simple architecture that enables the definition of this information natively in a semantic way, achieving the integration of the semantic information in the network packets. This will have several benefits, the most important being the possibility of promoting every WSN node to a real semantic information source.

Semantic integration of differently asynchronous audio-visual information in videos of real-world events in cognitive processing: an ERP study.

PubMed

Liu, Baolin; Wu, Guangning; Wang, Zhongning; Ji, Xiang

2011-07-01

In the real world, some of the auditory and visual information received by the human brain are temporally asynchronous. How is such information integrated in cognitive processing in the brain? In this paper, we aimed to study the semantic integration of differently asynchronous audio-visual information in cognitive processing using ERP (event-related potential) method. Subjects were presented with videos of real world events, in which the auditory and visual information are temporally asynchronous. When the critical action was prior to the sound, sounds incongruous with the preceding critical actions elicited a N400 effect when compared to congruous condition. This result demonstrates that semantic contextual integration indexed by N400 also applies to cognitive processing of multisensory information. In addition, the N400 effect is early in latency when contrasted with other visually induced N400 studies. It is shown that cross modal information is facilitated in time when contrasted with visual information in isolation. When the sound was prior to the critical action, a larger late positive wave was observed under the incongruous condition compared to congruous condition. P600 might represent a reanalysis process, in which the mismatch between the critical action and the preceding sound was evaluated. It is shown that environmental sound may affect the cognitive processing of a visual event. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Meaningful Memory in Acute Anorexia Nervosa Patients-Comparing Recall, Learning, and Recognition of Semantically Related and Semantically Unrelated Word Stimuli.

PubMed

Terhoeven, Valentin; Kallen, Ursula; Ingenerf, Katrin; Aschenbrenner, Steffen; Weisbrod, Matthias; Herzog, Wolfgang; Brockmeyer, Timo; Friederich, Hans-Christoph; Nikendei, Christoph

2017-03-01

It is unclear whether observed memory impairment in anorexia nervosa (AN) depends on the semantic structure (categorized words) of material to be encoded. We aimed to investigate the processing of semantically related information in AN. Memory performance was assessed in a recall, learning, and recognition test in 27 adult women with AN (19 restricting, 8 binge-eating/purging subtype; average disease duration: 9.32 years) and 30 healthy controls using an extended version of the Rey Auditory Verbal Learning Test, applying semantically related and unrelated word stimuli. Short-term memory (immediate recall, learning), regardless of semantics of the words, was significantly worse in AN patients, whereas long-term memory (delayed recall, recognition) did not differ between AN patients and controls. Semantics of stimuli do not have a better effect on memory recall in AN compared to CO. Impaired short-term versus long-term memory is discussed in relation to dysfunctional working memory in AN. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

Semantic transcoding of video based on regions of interest

NASA Astrophysics Data System (ADS)

Lim, Jeongyeon; Kim, Munchurl; Kim, Jong-Nam; Kim, Kyeongsoo

2003-06-01

Traditional transcoding on multimedia has been performed from the perspectives of user terminal capabilities such as display sizes and decoding processing power, and network resources such as available network bandwidth and quality of services (QoS) etc. The adaptation (or transcoding) of multimedia contents to given such constraints has been made by frame dropping and resizing of audiovisual, as well as reduction of SNR (Signal-to-Noise Ratio) values by saving the resulting bitrates. Not only such traditional transcoding is performed from the perspective of user"s environment, but also we incorporate a method of semantic transcoding of audiovisual based on region of interest (ROI) from user"s perspective. Users can designate their interested parts in images or video so that the corresponding video contents can be adapted focused on the user"s ROI. We incorporate the MPEG-21 DIA (Digital Item Adaptation) framework in which such semantic information of the user"s ROI is represented and delivered to the content provider side as XDI (context digital item). Representation schema of our semantic information of the user"s ROI has been adopted in MPEG-21 DIA Adaptation Model. In this paper, we present the usage of semantic information of user"s ROI for transcoding and show our system implementation with experimental results.

A user-centred evaluation framework for the Sealife semantic web browsers

PubMed Central

Oliver, Helen; Diallo, Gayo; de Quincey, Ed; Alexopoulou, Dimitra; Habermann, Bianca; Kostkova, Patty; Schroeder, Michael; Jupp, Simon; Khelif, Khaled; Stevens, Robert; Jawaheer, Gawesh; Madle, Gemma

2009-01-01

Background Semantically-enriched browsing has enhanced the browsing experience by providing contextualised dynamically generated Web content, and quicker access to searched-for information. However, adoption of Semantic Web technologies is limited and user perception from the non-IT domain sceptical. Furthermore, little attention has been given to evaluating semantic browsers with real users to demonstrate the enhancements and obtain valuable feedback. The Sealife project investigates semantic browsing and its application to the life science domain. Sealife's main objective is to develop the notion of context-based information integration by extending three existing Semantic Web browsers (SWBs) to link the existing Web to the eScience infrastructure. Methods This paper describes a user-centred evaluation framework that was developed to evaluate the Sealife SWBs that elicited feedback on users' perceptions on ease of use and information findability. Three sources of data: i) web server logs; ii) user questionnaires; and iii) semi-structured interviews were analysed and comparisons made between each browser and a control system. Results It was found that the evaluation framework used successfully elicited users' perceptions of the three distinct SWBs. The results indicate that the browser with the most mature and polished interface was rated higher for usability, and semantic links were used by the users of all three browsers. Conclusion Confirmation or contradiction of our original hypotheses with relation to SWBs is detailed along with observations of implementation issues. PMID:19796398

Clinical information modeling processes for semantic interoperability of electronic health records: systematic review and inductive analysis.

PubMed

Moreno-Conde, Alberto; Moner, David; Cruz, Wellington Dimas da; Santos, Marcelo R; Maldonado, José Alberto; Robles, Montserrat; Kalra, Dipak

2015-07-01

This systematic review aims to identify and compare the existing processes and methodologies that have been published in the literature for defining clinical information models (CIMs) that support the semantic interoperability of electronic health record (EHR) systems. Following the preferred reporting items for systematic reviews and meta-analyses systematic review methodology, the authors reviewed published papers between 2000 and 2013 that covered that semantic interoperability of EHRs, found by searching the PubMed, IEEE Xplore, and ScienceDirect databases. Additionally, after selection of a final group of articles, an inductive content analysis was done to summarize the steps and methodologies followed in order to build CIMs described in those articles. Three hundred and seventy-eight articles were screened and thirty six were selected for full review. The articles selected for full review were analyzed to extract relevant information for the analysis and characterized according to the steps the authors had followed for clinical information modeling. Most of the reviewed papers lack a detailed description of the modeling methodologies used to create CIMs. A representative example is the lack of description related to the definition of terminology bindings and the publication of the generated models. However, this systematic review confirms that most clinical information modeling activities follow very similar steps for the definition of CIMs. Having a robust and shared methodology could improve their correctness, reliability, and quality. Independently of implementation technologies and standards, it is possible to find common patterns in methods for developing CIMs, suggesting the viability of defining a unified good practice methodology to be used by any clinical information modeler. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Effects of donepezil on verbal memory after semantic processing in healthy older adults.

PubMed

FitzGerald, David B; Crucian, Gregory P; Mielke, Jeannine B; Shenal, Brian V; Burks, David; Womack, Kyle B; Ghacibeh, Georges; Drago, Valeria; Foster, Paul S; Valenstein, Edward; Heilman, Kenneth M

2008-06-01

To learn if acetylcholinesterase inhibitors alter verbal recall by improving semantic encoding in a double-blind randomized placebo-controlled trial. Cholinergic supplementation has been shown to improve delayed recall in adults with Alzheimer disease. With functional magnetic resonance imaging, elderly adults, when compared with younger participants, have reduced cortical activation with semantic processing. There have been no studies investigating the effects of cholinergic supplementation on semantic encoding in healthy elderly adults. Twenty elderly participants (mean age 71.5, SD+/-5.2) were recruited. All underwent memory testing before and after receiving donepezil (5 mg, n=11 or 10 mg, n=1) or placebo (n=8) for 6 weeks. Memory was tested using a Levels of Processing task, where a series of words are presented serially. Subjects were either asked to count consonants in a word (superficially process) or decide if the word was "pleasant" or "unpleasant" (semantically process). After 6 weeks of donepezil or placebo treatment, immediate and delayed recall of superficially and semantically processed words was compared with baseline performance. Immediate and delayed recall of superficially processed words did not show significant changes in either treatment group. With semantic processing, both immediate and delayed recall performance improved in the donepezil group. Our results suggest that when using semantic encoding, older normal subjects may be aided by anticholinesterase treatment. However, this treatment does not improve recall of superficially encoded words.

Semantic modeling and structural synthesis of onboard electronics protection means as open information system

NASA Astrophysics Data System (ADS)

Zhevnerchuk, D. V.; Surkova, A. S.; Lomakina, L. S.; Golubev, A. S.

2018-05-01

The article describes the component representation approach and semantic models of on-board electronics protection from ionizing radiation of various nature. Semantic models are constructed, the feature of which is the representation of electronic elements, protection modules, sources of impact in the form of blocks with interfaces. The rules of logical inference and algorithms for synthesizing the object properties of the semantic network, imitating the interface between the components of the protection system and the sources of radiation, are developed. The results of the algorithm are considered using the example of radiation-resistant microcircuits 1645RU5U, 1645RT2U and the calculation and experimental method for estimating the durability of on-board electronics.

Informatics in radiology: radiology gamuts ontology: differential diagnosis for the Semantic Web.

PubMed

Budovec, Joseph J; Lam, Cesar A; Kahn, Charles E

2014-01-01

The Semantic Web is an effort to add semantics, or "meaning," to empower automated searching and processing of Web-based information. The overarching goal of the Semantic Web is to enable users to more easily find, share, and combine information. Critical to this vision are knowledge models called ontologies, which define a set of concepts and formalize the relations between them. Ontologies have been developed to manage and exploit the large and rapidly growing volume of information in biomedical domains. In diagnostic radiology, lists of differential diagnoses of imaging observations, called gamuts, provide an important source of knowledge. The Radiology Gamuts Ontology (RGO) is a formal knowledge model of differential diagnoses in radiology that includes 1674 differential diagnoses, 19,017 terms, and 52,976 links between terms. Its knowledge is used to provide an interactive, freely available online reference of radiology gamuts ( www.gamuts.net ). A Web service allows its content to be discovered and consumed by other information systems. The RGO integrates radiologic knowledge with other biomedical ontologies as part of the Semantic Web. © RSNA, 2014.

e-Science and biological pathway semantics

PubMed Central

Luciano, Joanne S; Stevens, Robert D

2007-01-01

Background The development of e-Science presents a major set of opportunities and challenges for the future progress of biological and life scientific research. Major new tools are required and corresponding demands are placed on the high-throughput data generated and used in these processes. Nowhere is the demand greater than in the semantic integration of these data. Semantic Web tools and technologies afford the chance to achieve this semantic integration. Since pathway knowledge is central to much of the scientific research today it is a good test-bed for semantic integration. Within the context of biological pathways, the BioPAX initiative, part of a broader movement towards the standardization and integration of life science databases, forms a necessary prerequisite for its successful application of e-Science in health care and life science research. This paper examines whether BioPAX, an effort to overcome the barrier of disparate and heterogeneous pathway data sources, addresses the needs of e-Science. Results We demonstrate how BioPAX pathway data can be used to ask and answer some useful biological questions. We find that BioPAX comes close to meeting a broad range of e-Science needs, but certain semantic weaknesses mean that these goals are missed. We make a series of recommendations for re-modeling some aspects of BioPAX to better meet these needs. Conclusion Once these semantic weaknesses are addressed, it will be possible to integrate pathway information in a manner that would be useful in e-Science. PMID:17493286

Semantic similarity measure in biomedical domain leverage web search engine.

PubMed

Chen, Chi-Huang; Hsieh, Sheau-Ling; Weng, Yung-Ching; Chang, Wen-Yung; Lai, Feipei

2010-01-01

Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

The MMI Semantic Framework: Rosetta Stones for Earth Sciences

NASA Astrophysics Data System (ADS)

Rueda, C.; Bermudez, L. E.; Graybeal, J.; Alexander, P.

2009-12-01

Semantic interoperability—the exchange of meaning among computer systems—is needed to successfully share data in Ocean Science and across all Earth sciences. The best approach toward semantic interoperability requires a designed framework, and operationally tested tools and infrastructure within that framework. Currently available technologies make a scientific semantic framework feasible, but its development requires sustainable architectural vision and development processes. This presentation outlines the MMI Semantic Framework, including recent progress on it and its client applications. The MMI Semantic Framework consists of tools, infrastructure, and operational and community procedures and best practices, to meet short-term and long-term semantic interoperability goals. The design and prioritization of the semantic framework capabilities are based on real-world scenarios in Earth observation systems. We describe some key uses cases, as well as the associated requirements for building the overall infrastructure, which is realized through the MMI Ontology Registry and Repository. This system includes support for community creation and sharing of semantic content, ontology registration, version management, and seamless integration of user-friendly tools and application programming interfaces. The presentation describes the architectural components for semantic mediation, registry and repository for vocabularies, ontology, and term mappings. We show how the technologies and approaches in the framework can address community needs for managing and exchanging semantic information. We will demonstrate how different types of users and client applications exploit the tools and services for data aggregation, visualization, archiving, and integration. Specific examples from OOSTethys (http://www.oostethys.org) and the Ocean Observatories Initiative Cyberinfrastructure (http://www.oceanobservatories.org) will be cited. Finally, we show how semantic augmentation of web

Personal semantics: at the crossroads of semantic and episodic memory.

PubMed

Renoult, Louis; Davidson, Patrick S R; Palombo, Daniela J; Moscovitch, Morris; Levine, Brian

2012-11-01

Declarative memory is usually described as consisting of two systems: semantic and episodic memory. Between these two poles, however, may lie a third entity: personal semantics (PS). PS concerns knowledge of one's past. Although typically assumed to be an aspect of semantic memory, it is essentially absent from existing models of knowledge. Furthermore, like episodic memory (EM), PS is idiosyncratically personal (i.e., not culturally-shared). We show that, depending on how it is operationalized, the neural correlates of PS can look more similar to semantic memory, more similar to EM, or dissimilar to both. We consider three different perspectives to better integrate PS into existing models of declarative memory and suggest experimental strategies for disentangling PS from semantic and episodic memory. Copyright © 2012 Elsevier Ltd. All rights reserved.

Semantic and Phonological Activation in First and Second Language Reading

ERIC Educational Resources Information Center

Cheng, Hui-Wen

2012-01-01

No consensus has been reached on whether phonological information is activated in reading Chinese. Further, semantic activation has not been well-studied in the context of orthographic depth. To contribute to these issues, this dissertation investigated semantic and phonological activation in reading Chinese and English. This dissertation also…

SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services.

PubMed

Gessler, Damian D G; Schiltz, Gary S; May, Greg D; Avraham, Shulamit; Town, Christopher D; Grant, David; Nelson, Rex T

2009-09-23

SSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies. There are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at http://sswap.info (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at http://sswap.info/protocol.jsp, developer tools at http://sswap.info/developer.jsp, and a portal to third-party ontologies at http://sswapmeet.sswap.info (a "swap meet"). SSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the

SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services

PubMed Central

Gessler, Damian DG; Schiltz, Gary S; May, Greg D; Avraham, Shulamit; Town, Christopher D; Grant, David; Nelson, Rex T

2009-01-01

Background SSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies. Results There are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at , developer tools at , and a portal to third-party ontologies at (a "swap meet"). Conclusion SSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the confounding of content, structure, and presentation. SSWAP is novel by establishing

An individual differences approach to semantic cognition: Divergent effects of age on representation, retrieval and selection.

PubMed

Hoffman, Paul

2018-05-25

Semantic cognition refers to the appropriate use of acquired knowledge about the world. This requires representation of knowledge as well as control processes which ensure that currently-relevant aspects of knowledge are retrieved and selected. Although these abilities can be impaired selectively following brain damage, the relationship between them in healthy individuals is unclear. It is also commonly assumed that semantic cognition is preserved in later life, because older people have greater reserves of knowledge. However, this claim overlooks the possibility of decline in semantic control processes. Here, semantic cognition was assessed in 100 young and older adults. Despite having a broader knowledge base, older people showed specific impairments in semantic control, performing more poorly than young people when selecting among competing semantic representations. Conversely, they showed preserved controlled retrieval of less salient information from the semantic store. Breadth of semantic knowledge was positively correlated with controlled retrieval but was unrelated to semantic selection ability, which was instead correlated with non-semantic executive function. These findings indicate that three distinct elements contribute to semantic cognition: semantic representations that accumulate throughout the lifespan, processes for controlled retrieval of less salient semantic information, which appear age-invariant, and mechanisms for selecting task-relevant aspects of semantic knowledge, which decline with age and may relate more closely to domain-general executive control.

Semantic Learning Modifies Perceptual Face Processing

ERIC Educational Resources Information Center

Heisz, Jennifer J.; Shedden, Judith M.

2009-01-01

Face processing changes when a face is learned with personally relevant information. In a five-day learning paradigm, faces were presented with rich semantic stories that conveyed personal information about the faces. Event-related potentials were recorded before and after learning during a passive viewing task. When faces were novel, we observed…

Measuring content overlap during handoff communication using distributional semantics: An exploratory study.

PubMed

Abraham, Joanna; Kannampallil, Thomas G; Srinivasan, Vignesh; Galanter, William L; Tagney, Gail; Cohen, Trevor

2017-01-01

We develop and evaluate a methodological approach to measure the degree and nature of overlap in handoff communication content within and across clinical professions. This extensible, exploratory approach relies on combining techniques from conversational analysis and distributional semantics. We audio-recorded handoff communication of residents and nurses on the General Medicine floor of a large academic hospital (n=120 resident and n=120 nurse handoffs). We measured semantic similarity, a proxy for content overlap, between resident-resident and nurse-nurse communication using multiple steps: a qualitative conversational content analysis; an automated semantic similarity analysis using Reflective Random Indexing (RRI); and comparing semantic similarity generated by RRI analysis with human ratings of semantic similarity. There was significant association between the semantic similarity as computed by the RRI method and human rating (ρ=0.88). Based on the semantic similarity scores, content overlap was relatively higher for content related to patient active problems, assessment of active problems, patient-identifying information, past medical history, and medications/treatments. In contrast, content overlap was limited on content related to allergies, family-related information, code status, and anticipatory guidance. Our approach using RRI analysis provides new opportunities for characterizing the nature and degree of overlap in handoff communication. Although exploratory, this method provides a basis for identifying content that can be used for determining shared understanding across clinical professions. Additionally, this approach can inform the development of flexibly standardized handoff tools that reflect clinical content that are most appropriate for fostering shared understanding during transitions of care. Copyright © 2016 Elsevier Inc. All rights reserved.

Instructions to suppress semantic memory enhances or has no effect on P300 in a concealed information test (CIT).

PubMed

Rosenfeld, J Peter; Ward, Anne; Drapekin, Jesse; Labkovsky, Elena; Tullman, Samuel

2017-03-01

The present study investigated the extent to which people can suppress semantic memory as indexed with the P300 ERP and the autobiographical implicit association test (aIAT). In EXP 1, participants (22) were run in a counterbalanced repeated measures study in both simply knowledgeable (SK) and knowledgeable with suppression (SP) conditions. A P300-based, concealed information test ("Complex Trial Protocol"; CTP) with a 50/50 Target/Nontarget (T/NT) ratio was given both with and without instructions to suppress semantic memories. The results showed increased P300s to probe name stimuli, reduced (but still high positive) aIAT d-scores, and increased simple reaction times to all stimuli used in ERP tests in the SP condition. EXP 2 was similar, but with SP and SK in two separate groups, and a 20/80 T/NT ratio. Again, ERP and aIAT results failed to show a suppression effect for semantic memory. The behavioral data suggest some task demand effects under suppression instructions, and that EXP 1 was more demanding than EXP 2. Copyright © 2017 Elsevier B.V. All rights reserved.

A semantic web framework to integrate cancer omics data with biological knowledge

PubMed Central

2012-01-01

Background The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. Results For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. Conclusions We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily. PMID:22373303

A semantic web framework to integrate cancer omics data with biological knowledge.

PubMed

Holford, Matthew E; McCusker, James P; Cheung, Kei-Hoi; Krauthammer, Michael

2012-01-25

The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.

Functional Semantics.

DTIC Science & Technology

1982-01-01

teory. TD T .... A PR 4 983 Dr. H uare’s reerc was supported by the Air Force Office of Scientific Research (Contract F49620-S0-C-000 I). CoMpO , was...REPORTOATIf., Mathematical & Information Sciences Directorate Air Force Office of Scientific Research -1. NUMBER OF AGE Bolling AFB DC 20332 31 14...programs, that is, prove things about them and their specifications. This pqe describes the so- called "functional semantics" of Mills [8,9], which combines

Towards a framework for developing semantic relatedness reference standards.

PubMed

Pakhomov, Serguei V S; Pedersen, Ted; McInnes, Bridget; Melton, Genevieve B; Ruggieri, Alexander; Chute, Christopher G

2011-04-01

Our objective is to develop a framework for creating reference standards for functional testing of computerized measures of semantic relatedness. Currently, research on computerized approaches to semantic relatedness between biomedical concepts relies on reference standards created for specific purposes using a variety of methods for their analysis. In most cases, these reference standards are not publicly available and the published information provided in manuscripts that evaluate computerized semantic relatedness measurement approaches is not sufficient to reproduce the results. Our proposed framework is based on the experiences of medical informatics and computational linguistics communities and addresses practical and theoretical issues with creating reference standards for semantic relatedness. We demonstrate the use of the framework on a pilot set of 101 medical term pairs rated for semantic relatedness by 13 medical coding experts. While the reliability of this particular reference standard is in the "moderate" range; we show that using clustering and factor analyses offers a data-driven approach to finding systematic differences among raters and identifying groups of potential outliers. We test two ontology-based measures of relatedness and provide both the reference standard containing individual ratings and the R program used to analyze the ratings as open-source. Currently, these resources are intended to be used to reproduce and compare results of studies involving computerized measures of semantic relatedness. Our framework may be extended to the development of reference standards in other research areas in medical informatics including automatic classification, information retrieval from medical records and vocabulary/ontology development. Copyright © 2010 Elsevier Inc. All rights reserved.

Towards a Framework for Developing Semantic Relatedness Reference Standards

PubMed Central

Pakhomov, Serguei V.S.; Pedersen, Ted; McInnes, Bridget; Melton, Genevieve B.; Ruggieri, Alexander; Chute, Christopher G.

2010-01-01

Our objective is to develop a framework for creating reference standards for functional testing of computerized measures of semantic relatedness. Currently, research on computerized approaches to semantic relatedness between biomedical concepts relies on reference standards created for specific purposes using a variety of methods for their analysis. In most cases, these reference standards are not publicly available and the published information provided in manuscripts that evaluate computerized semantic relatedness measurement approaches is not sufficient to reproduce the results. Our proposed framework is based on the experiences of medical informatics and computational linguistics communities and addresses practical and theoretical issues with creating reference standards for semantic relatedness. We demonstrate the use of the framework on a pilot set of 101 medical term pairs rated for semantic relatedness by 13 medical coding experts. While the reliability of this particular reference standard is in the “moderate” range; we show that using clustering and factor analyses offers a data-driven approach to finding systematic differences among raters and identifying groups of potential outliers. We test two ontology-based measures of relatedness and provide both the reference standard containing individual ratings and the R program used to analyze the ratings as open-source. Currently, these resources are intended to be used to reproduce and compare results of studies involving computerized measures of semantic relatedness. Our framework may be extended to the development of reference standards in other research areas in medical informatics including automatic classification, information retrieval from medical records and vocabulary/ontology development. PMID:21044697

Semantic Typicality Effects in Acquired Dyslexia: Evidence for Semantic Impairment in Deep Dyslexia.

PubMed

Riley, Ellyn A; Thompson, Cynthia K

2010-06-01

BACKGROUND: Acquired deep dyslexia is characterized by impairment in grapheme-phoneme conversion and production of semantic errors in oral reading. Several theories have attempted to explain the production of semantic errors in deep dyslexia, some proposing that they arise from impairments in both grapheme-phoneme and lexical-semantic processing, and others proposing that such errors stem from a deficit in phonological production. Whereas both views have gained some acceptance, the limited evidence available does not clearly eliminate the possibility that semantic errors arise from a lexical-semantic input processing deficit. AIMS: To investigate semantic processing in deep dyslexia, this study examined the typicality effect in deep dyslexic individuals, phonological dyslexic individuals, and controls using an online category verification paradigm. This task requires explicit semantic access without speech production, focusing observation on semantic processing from written or spoken input. METHODS #ENTITYSTARTX00026; PROCEDURES: To examine the locus of semantic impairment, the task was administered in visual and auditory modalities with reaction time as the primary dependent measure. Nine controls, six phonological dyslexic participants, and five deep dyslexic participants completed the study. OUTCOMES #ENTITYSTARTX00026; RESULTS: Controls and phonological dyslexic participants demonstrated a typicality effect in both modalities, while deep dyslexic participants did not demonstrate a typicality effect in either modality. CONCLUSIONS: These findings suggest that deep dyslexia is associated with a semantic processing deficit. Although this does not rule out the possibility of concomitant deficits in other modules of lexical-semantic processing, this finding suggests a direction for treatment of deep dyslexia focused on semantic processing.

Varieties of semantic ‘access’ deficit in Wernicke’s aphasia and semantic aphasia

PubMed Central

Robson, Holly; Lambon Ralph, Matthew A.; Jefferies, Elizabeth

2015-01-01

Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke’s aphasia, associated with poor auditory–verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic ‘access’ deficit, as opposed to the ‘storage’ deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of ‘access’ impairment—related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke’s aphasia). We used a case series design to compare patients with Wernicke’s aphasia and those with semantic aphasia on Warrington’s paradigmatic assessment of semantic ‘access’ deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic ‘blocking’ effects). Patients with Wernicke’s aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability—one that mapped onto classical ‘syndromes’ and one that did not—predicted aspects of the semantic ‘access’ deficit. Both semantic aphasia and Wernicke’s aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke’s aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially �

Semantic Image Segmentation with Contextual Hierarchical Models.

PubMed

Seyedhosseini, Mojtaba; Tasdizen, Tolga

2016-05-01

Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

Populating the Semantic Web by Macro-reading Internet Text

NASA Astrophysics Data System (ADS)

Mitchell, Tom M.; Betteridge, Justin; Carlson, Andrew; Hruschka, Estevam; Wang, Richard

A key question regarding the future of the semantic web is "how will we acquire structured information to populate the semantic web on a vast scale?" One approach is to enter this information manually. A second approach is to take advantage of pre-existing databases, and to develop common ontologies, publishing standards, and reward systems to make this data widely accessible. We consider here a third approach: developing software that automatically extracts structured information from unstructured text present on the web. We also describe preliminary results demonstrating that machine learning algorithms can learn to extract tens of thousands of facts to populate a diverse ontology, with imperfect but reasonably good accuracy.

Enhanced semantic interoperability by profiling health informatics standards.

PubMed

López, Diego M; Blobel, Bernd

2009-01-01

Several standards applied to the healthcare domain support semantic interoperability. These standards are far from being completely adopted in health information system development, however. The objective of this paper is to provide a method and suggest the necessary tooling for reusing standard health information models, by that way supporting the development of semantically interoperable systems and components. The approach is based on the definition of UML Profiles. UML profiling is a formal modeling mechanism to specialize reference meta-models in such a way that it is possible to adapt those meta-models to specific platforms or domains. A health information model can be considered as such a meta-model. The first step of the introduced method identifies the standard health information models and tasks in the software development process in which healthcare information models can be reused. Then, the selected information model is formalized as a UML Profile. That Profile is finally applied to system models, annotating them with the semantics of the information model. The approach is supported on Eclipse-based UML modeling tools. The method is integrated into a comprehensive framework for health information systems development, and the feasibility of the approach is demonstrated in the analysis, design, and implementation of a public health surveillance system, reusing HL7 RIM and DIMs specifications. The paper describes a method and the necessary tooling for reusing standard healthcare information models. UML offers several advantages such as tooling support, graphical notation, exchangeability, extensibility, semi-automatic code generation, etc. The approach presented is also applicable for harmonizing different standard specifications.

[Effects of punctuation on the processing of syntactically ambiguous Japanese sentences with a semantic bias].

PubMed

Niikuni, Keiyu; Muramoto, Toshiaki

2014-06-01

This study explored the effects of a comma on the processing of structurally ambiguous Japanese sentences with a semantic bias. A previous study has shown that a comma which is incompatible with an ambiguous sentence's semantic bias affects the processing of the sentence, but the effects of a comma that is compatible with the bias are unclear. In the present study, we examined the role of a comma compatible with the sentence's semantic bias using the self-paced reading method, which enabled us to determine the reading times for the region of the sentence where readers would be expected to solve the ambiguity using semantic information (the "target region"). The results show that a comma significantly increases the reading time of the punctuated word but decreases the reading time in the target region. We concluded that even if the semantic information provided might be sufficient for disambiguation, the insertion of a comma would affect the processing cost of the ambiguity, indicating that readers use both the comma and semantic information in parallel for sentence processing.

Towards comprehensive syntactic and semantic annotations of the clinical narrative

PubMed Central

Albright, Daniel; Lanfranchi, Arrick; Fredriksen, Anwen; Styler, William F; Warner, Colin; Hwang, Jena D; Choi, Jinho D; Dligach, Dmitriy; Nielsen, Rodney D; Martin, James; Ward, Wayne; Palmer, Martha; Savova, Guergana K

2013-01-01

Objective To create annotated clinical narratives with layers of syntactic and semantic labels to facilitate advances in clinical natural language processing (NLP). To develop NLP algorithms and open source components. Methods Manual annotation of a clinical narrative corpus of 127 606 tokens following the Treebank schema for syntactic information, PropBank schema for predicate-argument structures, and the Unified Medical Language System (UMLS) schema for semantic information. NLP components were developed. Results The final corpus consists of 13 091 sentences containing 1772 distinct predicate lemmas. Of the 766 newly created PropBank frames, 74 are verbs. There are 28 539 named entity (NE) annotations spread over 15 UMLS semantic groups, one UMLS semantic type, and the Person semantic category. The most frequent annotations belong to the UMLS semantic groups of Procedures (15.71%), Disorders (14.74%), Concepts and Ideas (15.10%), Anatomy (12.80%), Chemicals and Drugs (7.49%), and the UMLS semantic type of Sign or Symptom (12.46%). Inter-annotator agreement results: Treebank (0.926), PropBank (0.891–0.931), NE (0.697–0.750). The part-of-speech tagger, constituency parser, dependency parser, and semantic role labeler are built from the corpus and released open source. A significant limitation uncovered by this project is the need for the NLP community to develop a widely agreed-upon schema for the annotation of clinical concepts and their relations. Conclusions This project takes a foundational step towards bringing the field of clinical NLP up to par with NLP in the general domain. The corpus creation and NLP components provide a resource for research and application development that would have been previously impossible. PMID:23355458

A Graph-Based Recovery and Decomposition of Swanson’s Hypothesis using Semantic Predications

PubMed Central

Cameron, Delroy; Bodenreider, Olivier; Yalamanchili, Hima; Danh, Tu; Vallabhaneni, Sreeram; Thirunarayan, Krishnaprasad; Sheth, Amit P.; Rindflesch, Thomas C.

2014-01-01

Objectives This paper presents a methodology for recovering and decomposing Swanson’s Raynaud Syndrome–Fish Oil Hypothesis semi-automatically. The methodology leverages the semantics of assertions extracted from biomedical literature (called semantic predications) along with structured background knowledge and graph-based algorithms to semi-automatically capture the informative associations originally discovered manually by Swanson. Demonstrating that Swanson’s manually intensive techniques can be undertaken semi-automatically, paves the way for fully automatic semantics-based hypothesis generation from scientific literature. Methods Semantic predications obtained from biomedical literature allow the construction of labeled directed graphs which contain various associations among concepts from the literature. By aggregating such associations into informative subgraphs, some of the relevant details originally articulated by Swanson has been uncovered. However, by leveraging background knowledge to bridge important knowledge gaps in the literature, a methodology for semi-automatically capturing the detailed associations originally explicated in natural language by Swanson has been developed. Results Our methodology not only recovered the 3 associations commonly recognized as Swanson’s Hypothesis, but also decomposed them into an additional 16 detailed associations, formulated as chains of semantic predications. Altogether, 14 out of the 19 associations that can be attributed to Swanson were retrieved using our approach. To the best of our knowledge, such an in-depth recovery and decomposition of Swanson’s Hypothesis has never been attempted. Conclusion In this work therefore, we presented a methodology for semi- automatically recovering and decomposing Swanson’s RS-DFO Hypothesis using semantic representations and graph algorithms. Our methodology provides new insights into potential prerequisites for semantics-driven Literature-Based Discovery (LBD

Beyond the VWFA: The orthography-semantics interface in spelling and reading

PubMed Central

Purcell, Jeremy J.; Shea, Jennifer; Rapp, Brenda

2014-01-01

Lexical orthographic information provides the basis for recovering the meanings of words in reading and for generating correct word spellings in writing. Research has provided evidence that an area of the left ventral temporal cortex, a sub-region of what is often referred to as the Visual Word Form Area (VWFA), plays a significant role specifically in lexical orthographic processing. The current investigation goes beyond this previous work by examining the neurotopography of the interface of lexical orthography with semantics. We apply a novel lesion mapping approach with three individuals with acquired dysgraphia and dyslexia who suffered lesions to left ventral temporal cortex. To map cognitive processes to their neural substrates, this lesion mapping approach applies similar logical constraints as used in cognitive neuropsychological research. Using this approach, this investigation: (1) Identifies a region anterior to the VWFA that is important in the interface of orthographic information with semantics for reading and spelling; (2) Determines that, within this Orthography-Semantics Interface Region (OSIR), access to orthography from semantics (spelling) is topographically distinct from access to semantics from orthography (reading); (3) Provides evidence that, within this region, there is modality-specific access to and from lexical semantics for both spoken and written modalities, in both word production and comprehension. Overall, this study contributes to our understanding of the neural architecture at the lexical orthography-semantic-phonological interface within left ventral temporal cortex. PMID:24833190

The semantic richness of abstract concepts

PubMed Central

Recchia, Gabriel; Jones, Michael N.

2012-01-01

We contrasted the predictive power of three measures of semantic richness—number of features (NFs), contextual dispersion (CD), and a novel measure of number of semantic neighbors (NSN)—for a large set of concrete and abstract concepts on lexical decision and naming tasks. NSN (but not NF) facilitated processing for abstract concepts, while NF (but not NSN) facilitated processing for the most concrete concepts, consistent with claims that linguistic information is more relevant for abstract concepts in early processing. Additionally, converging evidence from two datasets suggests that when NSN and CD are controlled for, the features that most facilitate processing are those associated with a concept's physical characteristics and real-world contexts. These results suggest that rich linguistic contexts (many semantic neighbors) facilitate early activation of abstract concepts, whereas concrete concepts benefit more from rich physical contexts (many associated objects and locations). PMID:23205008

Improving Semantic Updating Method on 3d City Models Using Hybrid Semantic-Geometric 3d Segmentation Technique

NASA Astrophysics Data System (ADS)

Sharkawi, K.-H.; Abdul-Rahman, A.

2013-09-01

to LoD4. The accuracy and structural complexity of the 3D objects increases with the LoD level where LoD0 is the simplest LoD (2.5D; Digital Terrain Model (DTM) + building or roof print) while LoD4 is the most complex LoD (architectural details with interior structures). Semantic information is one of the main components in CityGML and 3D City Models, and provides important information for any analyses. However, more often than not, the semantic information is not available for the 3D city model due to the unstandardized modelling process. One of the examples is where a building is normally generated as one object (without specific feature layers such as Roof, Ground floor, Level 1, Level 2, Block A, Block B, etc). This research attempts to develop a method to improve the semantic data updating process by segmenting the 3D building into simpler parts which will make it easier for the users to select and update the semantic information. The methodology is implemented for 3D buildings in LoD2 where the buildings are generated without architectural details but with distinct roof structures. This paper also introduces hybrid semantic-geometric 3D segmentation method that deals with hierarchical segmentation of a 3D building based on its semantic value and surface characteristics, fitted by one of the predefined primitives. For future work, the segmentation method will be implemented as part of the change detection module that can detect any changes on the 3D buildings, store and retrieve semantic information of the changed structure, automatically updates the 3D models and visualize the results in a userfriendly graphical user interface (GUI).

Semantic Metadata for Heterogeneous Spatial Planning Documents

NASA Astrophysics Data System (ADS)

Iwaniak, A.; Kaczmarek, I.; Łukowicz, J.; Strzelecki, M.; Coetzee, S.; Paluszyński, W.

2016-09-01

Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Semantic Similarity of Labels and Inductive Generalization: Taking a Second Look

ERIC Educational Resources Information Center

Fisher, Anna V.; Matlen, Bryan J.; Godwin, Karrie E.

2011-01-01

Prior research suggests that preschoolers can generalize object properties based on category information conveyed by semantically-similar labels. However, previous research did not control for co-occurrence probability of labels in natural speech. The current studies re-assessed children's generalization with semantically-similar labels.…

Further differentiating item and order information in semantic memory: students' recall of words from the "CU Fight Song", Harry Potter book titles, and Scooby Doo theme song.

PubMed

Overstreet, Michael F; Healy, Alice F; Neath, Ian

2017-01-01

University of Colorado (CU) students were tested for both order and item information in their semantic memory for the "CU Fight Song". Following an earlier study by Overstreet and Healy [(2011). Item and order information in semantic memory: Students' retention of the "CU fight song" lyrics. Memory & Cognition, 39, 251-259. doi: 10.3758/s13421-010-0018-3 ], a symmetrical bow-shaped serial position function (with both primacy and recency advantages) was found for reconstructing the order of the nine lines in the song, whereas a function with no primacy advantage was found for recalling a missing word from each line. This difference between order and item information was found even though students filled in missing words without any alternatives provided and missing words came from the beginning, middle, or end of each line. Similar results were found for CU students' recall of the sequence of Harry Potter book titles and the lyrics of the Scooby Doo theme song. These findings strengthen the claim that the pronounced serial position function in semantic memory occurs largely because of the retention of order, rather than item, information.

Understanding human activity patterns based on space-time-semantics

NASA Astrophysics Data System (ADS)

Huang, Wei; Li, Songnian

2016-11-01

Understanding human activity patterns plays a key role in various applications in an urban environment, such as transportation planning and traffic forecasting, urban planning, public health and safety, and emergency response. Most existing studies in modeling human activity patterns mainly focus on spatiotemporal dimensions, which lacks consideration of underlying semantic context. In fact, what people do and discuss at some places, inferring what is happening at the places, cannot be simple neglected because it is the root of human mobility patterns. We believe that the geo-tagged semantic context, representing what individuals do and discuss at a place and a specific time, drives a formation of specific human activity pattern. In this paper, we aim to model human activity patterns not only based on space and time but also with consideration of associated semantics, and attempt to prove a hypothesis that similar mobility patterns may have different motivations. We develop a spatiotemporal-semantic model to quantitatively express human activity patterns based on topic models, leading to an analysis of space, time and semantics. A case study is conducted using Twitter data in Toronto based on our model. Through computing the similarities between users in terms of spatiotemporal pattern, semantic pattern and spatiotemporal-semantic pattern, we find that only a small number of users (2.72%) have very similar activity patterns, while the majority (87.14%) show different activity patterns (i.e., similar spatiotemporal patterns and different semantic patterns, similar semantic patterns and different spatiotemporal patterns, or different in both). The population of users that has very similar activity patterns is decreased by 56.41% after incorporating semantic information in the corresponding spatiotemporal patterns, which can quantitatively prove the hypothesis.

Sex differences in the use of delayed semantic context when listening to disrupted speech.

PubMed

Liederman, Jacqueline; Fisher, Janet McGraw; Coty, Alexis; Matthews, Geetha; Frye, Richard E; Lincoln, Alexis; Alexander, Rebecca

2013-02-01

Female as opposed to male listeners were better able to use a delayed informative cue at the end of a long sentence to report an earlier word which was disrupted by noise. Informative (semantically related) or uninformative (semantically unrelated) word cues were presented 2, 6, or 10 words after a target word whose initial phoneme had been replaced with noise. A total of 84 young adults (45 males) listened to each sentence and then repeated it after its offset. The semantic benefit effect (SBE) was the difference in the accuracy of report of the disrupted target word during informative vs. uninformative sentences. Women had significantly higher SBEs than men even though there were no significant sex differences in terms of number of non-target words reported, the effect of distance between the disrupted target word and the informative cue, or kinds of errors generated. We suggest that the superior ability of women to use delayed semantic information to decode an earlier ambiguous speech signal may be linked to women's tendency to engage the hemispheres more bilaterally than men during word processing. Since the maintenance of semantic context under ambiguous conditions demands more right than left hemispheric resources, this may give women an advantage.

Representations for Semantic Learning Webs: Semantic Web Technology in Learning Support

ERIC Educational Resources Information Center

Dzbor, M.; Stutt, A.; Motta, E.; Collins, T.

2007-01-01

Recent work on applying semantic technologies to learning has concentrated on providing novel means of accessing and making use of learning objects. However, this is unnecessarily limiting: semantic technologies will make it possible to develop a range of educational Semantic Web services, such as interpretation, structure-visualization, support…

Combinatorial semantics strengthens angular-anterior temporal coupling.

PubMed

Molinaro, Nicola; Paz-Alonso, Pedro M; Duñabeitia, Jon Andoni; Carreiras, Manuel

2015-04-01

The human semantic combinatorial system allows us to create a wide number of new meanings from a finite number of existing representations. The present study investigates the neural dynamics underlying the semantic processing of different conceptual constructions based on predictions from previous neuroanatomical models of the semantic processing network. In two experiments, participants read sentences for comprehension containing noun-adjective pairs in three different conditions: prototypical (Redundant), nonsense (Anomalous) and low-typical but composable (Contrastive). In Experiment 1 we examined the processing costs associated to reading these sentences and found a processing dissociation between Anomalous and Contrastive word pairs, compared to prototypical (Redundant) stimuli. In Experiment 2, functional connectivity results showed strong co-activation across conditions between inferior frontal gyrus (IFG) and posterior middle temporal gyrus (MTG), as well as between these two regions and middle frontal gyrus (MFG), anterior temporal cortex (ATC) and fusiform gyrus (FG), consistent with previous neuroanatomical models. Importantly, processing of low-typical (but composable) meanings relative to prototypical and anomalous constructions was associated with a stronger positive coupling between ATC and angular gyrus (AG). Our results underscore the critical role of IFG-MTG co-activation during semantic processing and how other relevant nodes within the semantic processing network come into play to handle visual-orthographic information, to maintain multiple lexical-semantic representations in working memory and to combine existing representations while creatively constructing meaning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Semantic Neighborhood Effects for Abstract versus Concrete Words.

PubMed

Danguecan, Ashley N; Buchanan, Lori

2016-01-01

Studies show that semantic effects may be task-specific, and thus, that semantic representations are flexible and dynamic. Such findings are critical to the development of a comprehensive theory of semantic processing in visual word recognition, which should arguably account for how semantic effects may vary by task. It has been suggested that semantic effects are more directly examined using tasks that explicitly require meaning processing relative to those for which meaning processing is not necessary (e.g., lexical decision task). The purpose of the present study was to chart the processing of concrete versus abstract words in the context of a global co-occurrence variable, semantic neighborhood density (SND), by comparing word recognition response times (RTs) across four tasks varying in explicit semantic demands: standard lexical decision task (with non-pronounceable non-words), go/no-go lexical decision task (with pronounceable non-words), progressive demasking task, and sentence relatedness task. The same experimental stimulus set was used across experiments and consisted of 44 concrete and 44 abstract words, with half of these being low SND, and half being high SND. In this way, concreteness and SND were manipulated in a factorial design using a number of visual word recognition tasks. A consistent RT pattern emerged across tasks, in which SND effects were found for abstract (but not necessarily concrete) words. Ultimately, these findings highlight the importance of studying interactive effects in word recognition, and suggest that linguistic associative information is particularly important for abstract words.

Semantics-Based Interoperability Framework for the Geosciences

NASA Astrophysics Data System (ADS)

Sinha, A.; Malik, Z.; Raskin, R.; Barnes, C.; Fox, P.; McGuinness, D.; Lin, K.

2008-12-01

Interoperability between heterogeneous data, tools and services is required to transform data to knowledge. To meet geoscience-oriented societal challenges such as forcing of climate change induced by volcanic eruptions, we suggest the need to develop semantic interoperability for data, services, and processes. Because such scientific endeavors require integration of multiple data bases associated with global enterprises, implicit semantic-based integration is impossible. Instead, explicit semantics are needed to facilitate interoperability and integration. Although different types of integration models are available (syntactic or semantic) we suggest that semantic interoperability is likely to be the most successful pathway. Clearly, the geoscience community would benefit from utilization of existing XML-based data models, such as GeoSciML, WaterML, etc to rapidly advance semantic interoperability and integration. We recognize that such integration will require a "meanings-based search, reasoning and information brokering", which will be facilitated through inter-ontology relationships (ontologies defined for each discipline). We suggest that Markup languages (MLs) and ontologies can be seen as "data integration facilitators", working at different abstraction levels. Therefore, we propose to use an ontology-based data registration and discovery approach to compliment mark-up languages through semantic data enrichment. Ontologies allow the use of formal and descriptive logic statements which permits expressive query capabilities for data integration through reasoning. We have developed domain ontologies (EPONT) to capture the concept behind data. EPONT ontologies are associated with existing ontologies such as SUMO, DOLCE and SWEET. Although significant efforts have gone into developing data (object) ontologies, we advance the idea of developing semantic frameworks for additional ontologies that deal with processes and services. This evolutionary step will

Investigating the capabilities of semantic enrichment of 3D CityEngine data

NASA Astrophysics Data System (ADS)

Solou, Dimitra; Dimopoulou, Efi

2016-08-01

In recent years the development of technology and the lifting of several technical limitations, has brought the third dimension to the fore. The complexity of urban environments and the strong need for land administration, intensify the need of using a three-dimensional cadastral system. Despite the progress in the field of geographic information systems and 3D modeling techniques, there is no fully digital 3D cadastre. The existing geographic information systems and the different methods of three-dimensional modeling allow for better management, visualization and dissemination of information. Nevertheless, these opportunities cannot be totally exploited because of deficiencies in standardization and interoperability in these systems. Within this context, CityGML was developed as an international standard of the Open Geospatial Consortium (OGC) for 3D city models' representation and exchange. CityGML defines geometry and topology for city modeling, also focusing on semantic aspects of 3D city information. The scope of CityGML is to reach common terminology, also addressing the imperative need for interoperability and data integration, taking into account the number of available geographic information systems and modeling techniques. The aim of this paper is to develop an application for managing semantic information of a model generated based on procedural modeling. The model was initially implemented in CityEngine ESRI's software, and then imported to ArcGIS environment. Final goal was the original model's semantic enrichment and then its conversion to CityGML format. Semantic information management and interoperability seemed to be feasible by the use of the 3DCities Project ESRI tools, since its database structure ensures adding semantic information to the CityEngine model and therefore automatically convert to CityGML for advanced analysis and visualization in different application areas.

A Validation of Parafoveal Semantic Information Extraction in Reading Chinese

ERIC Educational Resources Information Center

Zhou, Wei; Kliegl, Reinhold; Yan, Ming

2013-01-01

Parafoveal semantic processing has recently been well documented in reading Chinese sentences, presumably because of language-specific features. However, because of a large variation of fixation landing positions on pretarget words, some preview words actually were located in foveal vision when readers' eyes landed close to the end of the…

The effect of concurrent semantic categorization on delayed serial recall.

PubMed

Acheson, Daniel J; MacDonald, Maryellen C; Postle, Bradley R

2011-01-01

The influence of semantic processing on the serial ordering of items in short-term memory was explored using a novel dual-task paradigm. Participants engaged in 2 picture-judgment tasks while simultaneously performing delayed serial recall. List material varied in the presence of phonological overlap (Experiments 1 and 2) and in semantic content (concrete words in Experiment 1 and 3; nonwords in Experiments 2 and 3). Picture judgments varied in the extent to which they required accessing visual semantic information (i.e., semantic categorization and line orientation judgments). Results showed that, relative to line-orientation judgments, engaging in semantic categorization judgments increased the proportion of item-ordering errors for concrete lists but did not affect error proportions for nonword lists. Furthermore, although more ordering errors were observed for phonologically similar relative to dissimilar lists, no interactions were observed between the phonological overlap and picture-judgment task manipulations. These results demonstrate that lexical-semantic representations can affect the serial ordering of items in short-term memory. Furthermore, the dual-task paradigm provides a new method for examining when and how semantic representations affect memory performance.

The Effect of Concurrent Semantic Categorization on Delayed Serial Recall

PubMed Central

Acheson, Daniel J.; MacDonald, Maryellen C.; Postle, Bradley R.

2010-01-01

The influence of semantic processing on the serial ordering of items in short-term memory was explored using a novel dual-task paradigm. Subjects engaged in two picture judgment tasks while simultaneously performing delayed serial recall. List material varied in the presence of phonological overlap (Experiments 1 and 2) and in semantic content (concrete words in Experiment 1 and 3; nonwords in Experiments 2 and 3). Picture judgments varied in the extent to which they required accessing visual semantic information (i.e., semantic categorization and line orientation judgments). Results showed that, relative to line orientation judgments, engaging in semantic categorization judgments increased the proportion of item ordering errors for concrete lists but did not affect error proportions for nonword lists. Furthermore, although more ordering errors were observed for phonologically similar relative to dissimilar lists, no interactions were observed between the phonological overlap and picture judgment task manipulations. These results thus demonstrate that lexical-semantic representations can affect the serial ordering of items in short-term memory. Furthermore, the dual-task paradigm provides a new method for examining when and how semantic representations affect memory performance. PMID:21058880

Semantic Networks and Social Networks

ERIC Educational Resources Information Center

Downes, Stephen

2005-01-01

Purpose: To illustrate the need for social network metadata within semantic metadata. Design/methodology/approach: Surveys properties of social networks and the semantic web, suggests that social network analysis applies to semantic content, argues that semantic content is more searchable if social network metadata is merged with semantic web…

Treatment for Anomia in Semantic Dementia

PubMed Central

Henry, Maya L.; Beeson, Pélagie M.; Rapcsak, Steven Z.

2009-01-01

Anomia is a striking and consistent clinical feature of semantic dementia (SD), a progressive aphasia syndrome associated with focal cortical atrophy of the anterior temporal lobes. Word retrieval deficits in patients with SD have been attributed to the loss of conceptual knowledge, resulting in an impairment referred to as semantic anomia. Whereas an abundance of research has been dedicated to treatment for anomia in individuals with focal brain damage due to stroke, considerably less work has been done regarding treatment for patients with progressive language decline. The purpose of this article is to review the available literature concerning the nature and treatment of anomia in individuals with SD. Several studies have shown that new lexical learning remains possible in these patients. However, newly learned information is likely to be constrained by the learning context, and increased reliance on perceptual and autobiographical contextual information may be necessary to provide critical support for new vocabulary acquisition. There is also evidence suggesting that treatment may slow the progression of anomia over time, even affording some protective benefit to lexical items that are not yet lost. However, treatment efforts are likely to be most beneficial at early stages of the disease, when residual semantic knowledge as. well as relatively spared episodic memory may support new learning. PMID:18348092

Semantic memory in object use.

PubMed

Silveri, Maria Caterina; Ciccarelli, Nicoletta

2009-10-01

We studied five patients with semantic memory disorders, four with semantic dementia and one with herpes simplex virus encephalitis, to investigate the involvement of semantic conceptual knowledge in object use. Comparisons between patients who had semantic deficits of different severity, as well as the follow-up, showed that the ability to use objects was largely preserved when the deficit was mild but progressively decayed as the deficit became more severe. Naming was generally more impaired than object use. Production tasks (pantomime execution and actual object use) and comprehension tasks (pantomime recognition and action recognition) as well as functional knowledge about objects were impaired when the semantic deficit was severe. Semantic and unrelated errors were produced during object use, but actions were always fluent and patients performed normally on a novel tools task in which the semantic demand was minimal. Patients with severe semantic deficits scored borderline on ideational apraxia tasks. Our data indicate that functional semantic knowledge is crucial for using objects in a conventional way and suggest that non-semantic factors, mainly non-declarative components of memory, might compensate to some extent for semantic disorders and guarantee some residual ability to use very common objects independently of semantic knowledge.

A fusion network for semantic segmentation using RGB-D data

NASA Astrophysics Data System (ADS)

Yuan, Jiahui; Zhang, Kun; Xia, Yifan; Qi, Lin; Dong, Junyu

2018-04-01

Semantic scene parsing is considerable in many intelligent field, including perceptual robotics. For the past few years, pixel-wise prediction tasks like semantic segmentation with RGB images has been extensively studied and has reached very remarkable parsing levels, thanks to convolutional neural networks (CNNs) and large scene datasets. With the development of stereo cameras and RGBD sensors, it is expected that additional depth information will help improving accuracy. In this paper, we propose a semantic segmentation framework incorporating RGB and complementary depth information. Motivated by the success of fully convolutional networks (FCN) in semantic segmentation field, we design a fully convolutional networks consists of two branches which extract features from both RGB and depth data simultaneously and fuse them as the network goes deeper. Instead of aggregating multiple model, our goal is to utilize RGB data and depth data more effectively in a single model. We evaluate our approach on the NYU-Depth V2 dataset, which consists of 1449 cluttered indoor scenes, and achieve competitive results with the state-of-the-art methods.

The absoluteness of semantic processing: lessons from the analysis of temporal clusters in phonemic verbal fluency.

PubMed

Vonberg, Isabelle; Ehlen, Felicitas; Fromm, Ortwin; Klostermann, Fabian

2014-01-01

For word production, we may consciously pursue semantic or phonological search strategies, but it is uncertain whether we can retrieve the different aspects of lexical information independently from each other. We therefore studied the spread of semantic information into words produced under exclusively phonemic task demands. 42 subjects participated in a letter verbal fluency task, demanding the production of as many s-words as possible in two minutes. Based on curve fittings for the time courses of word production, output spurts (temporal clusters) considered to reflect rapid lexical retrieval based on automatic activation spread, were identified. Semantic and phonemic word relatedness within versus between these clusters was assessed by respective scores (0 meaning no relation, 4 maximum relation). Subjects produced 27.5 (±9.4) words belonging to 6.7 (±2.4) clusters. Both phonemically and semantically words were more related within clusters than between clusters (phon: 0.33±0.22 vs. 0.19±0.17, p<.01; sem: 0.65±0.29 vs. 0.37±0.29, p<.01). Whereas the extent of phonemic relatedness correlated with high task performance, the contrary was the case for the extent of semantic relatedness. The results indicate that semantic information spread occurs, even if the consciously pursued word search strategy is purely phonological. This, together with the negative correlation between semantic relatedness and verbal output suits the idea of a semantic default mode of lexical search, acting against rapid task performance in the given scenario of phonemic verbal fluency. The simultaneity of enhanced semantic and phonemic word relatedness within the same temporal cluster boundaries suggests an interaction between content and sound-related information whenever a new semantic field has been opened.

Remembering 'zeal' but not 'thing': reverse frequency effects as a consequence of deregulated semantic processing.

PubMed

Hoffman, Paul; Jefferies, Elizabeth; Ralph, Matthew A Lambon

2011-02-01

More efficient processing of high frequency (HF) words is a ubiquitous finding in healthy individuals, yet frequency effects are often small or absent in stroke aphasia. We propose that some patients fail to show the expected frequency effect because processing of HF words places strong demands on semantic control and regulation processes, counteracting the usual effect. This may occur because HF words appear in a wide range of linguistic contexts, each associated with distinct semantic information. This theory predicts that in extreme circumstances, patients with impaired semantic control should show an outright reversal of the normal frequency effect. To test this prediction, we tested two patients with impaired semantic control with a delayed repetition task that emphasised activation of semantic representations. By alternating HF and low frequency (LF) trials, we demonstrated a significant repetition advantage for LF words, principally because of perseverative errors in which patients produced the previous LF response in place of the HF target. These errors indicated that HF words were more weakly activated than LF words. We suggest that when presented with no contextual information, patients generate a weak and unstable pattern of semantic activation for HF words because information relating to many possible contexts and interpretations is activated. In contrast, LF words are associated with more stable patterns of activation because similar semantic information is activated whenever they are encountered. Copyright © 2011 Elsevier Ltd. All rights reserved.

Semantic Fission through Dialect Fusion.

ERIC Educational Resources Information Center

Linn, Michael D.

The linguistic atlas projects have provided much information on the regional distribution of pronunciation, vocabulary, and syntax and have given important evidence for a greater understanding of problems involved in semantic change, particularly in pointing out transition areas where dialects become fused. In a study supplementary to that…

Biomedical question answering using semantic relations.

PubMed

Hristovski, Dimitar; Dinevski, Dejan; Kastrin, Andrej; Rindflesch, Thomas C

2015-01-16

The proliferation of the scientific literature in the field of biomedicine makes it difficult to keep abreast of current knowledge, even for domain experts. While general Web search engines and specialized information retrieval (IR) systems have made important strides in recent decades, the problem of accurate knowledge extraction from the biomedical literature is far from solved. Classical IR systems usually return a list of documents that have to be read by the user to extract relevant information. This tedious and time-consuming work can be lessened with automatic Question Answering (QA) systems, which aim to provide users with direct and precise answers to their questions. In this work we propose a novel methodology for QA based on semantic relations extracted from the biomedical literature. We extracted semantic relations with the SemRep natural language processing system from 122,421,765 sentences, which came from 21,014,382 MEDLINE citations (i.e., the complete MEDLINE distribution up to the end of 2012). A total of 58,879,300 semantic relation instances were extracted and organized in a relational database. The QA process is implemented as a search in this database, which is accessed through a Web-based application, called SemBT (available at http://sembt.mf.uni-lj.si ). We conducted an extensive evaluation of the proposed methodology in order to estimate the accuracy of extracting a particular semantic relation from a particular sentence. Evaluation was performed by 80 domain experts. In total 7,510 semantic relation instances belonging to 2,675 distinct relations were evaluated 12,083 times. The instances were evaluated as correct 8,228 times (68%). In this work we propose an innovative methodology for biomedical QA. The system is implemented as a Web-based application that is able to provide precise answers to a wide range of questions. A typical question is answered within a few seconds. The tool has some extensions that make it especially useful for

Performance impact of stop lists and morphological decomposition on word-word corpus-based semantic space models.

PubMed

Keith, Jeff; Westbury, Chris; Goldman, James

2015-09-01

Corpus-based semantic space models, which primarily rely on lexical co-occurrence statistics, have proven effective in modeling and predicting human behavior in a number of experimental paradigms that explore semantic memory representation. The most widely studied extant models, however, are strongly influenced by orthographic word frequency (e.g., Shaoul & Westbury, Behavior Research Methods, 38, 190-195, 2006). This has the implication that high-frequency closed-class words can potentially bias co-occurrence statistics. Because these closed-class words are purported to carry primarily syntactic, rather than semantic, information, the performance of corpus-based semantic space models may be improved by excluding closed-class words (using stop lists) from co-occurrence statistics, while retaining their syntactic information through other means (e.g., part-of-speech tagging and/or affixes from inflected word forms). Additionally, very little work has been done to explore the effect of employing morphological decomposition on the inflected forms of words in corpora prior to compiling co-occurrence statistics, despite (controversial) evidence that humans perform early morphological decomposition in semantic processing. In this study, we explored the impact of these factors on corpus-based semantic space models. From this study, morphological decomposition appears to significantly improve performance in word-word co-occurrence semantic space models, providing some support for the claim that sublexical information-specifically, word morphology-plays a role in lexical semantic processing. An overall decrease in performance was observed in models employing stop lists (e.g., excluding closed-class words). Furthermore, we found some evidence that weakens the claim that closed-class words supply primarily syntactic information in word-word co-occurrence semantic space models.

Semantics based approach for analyzing disease-target associations.

PubMed

Kaalia, Rama; Ghosh, Indira

2016-08-01

A complex disease is caused by heterogeneous biological interactions between genes and their products along with the influence of environmental factors. There have been many attempts for understanding the cause of these diseases using experimental, statistical and computational methods. In the present work the objective is to address the challenge of representation and integration of information from heterogeneous biomedical aspects of a complex disease using semantics based approach. Semantic web technology is used to design Disease Association Ontology (DAO-db) for representation and integration of disease associated information with diabetes as the case study. The functional associations of disease genes are integrated using RDF graphs of DAO-db. Three semantic web based scoring algorithms (PageRank, HITS (Hyperlink Induced Topic Search) and HITS with semantic weights) are used to score the gene nodes on the basis of their functional interactions in the graph. Disease Association Ontology for Diabetes (DAO-db) provides a standard ontology-driven platform for describing genes, proteins, pathways involved in diabetes and for integrating functional associations from various interaction levels (gene-disease, gene-pathway, gene-function, gene-cellular component and protein-protein interactions). An automatic instance loader module is also developed in present work that helps in adding instances to DAO-db on a large scale. Our ontology provides a framework for querying and analyzing the disease associated information in the form of RDF graphs. The above developed methodology is used to predict novel potential targets involved in diabetes disease from the long list of loose (statistically associated) gene-disease associations. Copyright © 2016 Elsevier Inc. All rights reserved.

Towards Semantic Modelling of Business Processes for Networked Enterprises

NASA Astrophysics Data System (ADS)

Furdík, Karol; Mach, Marián; Sabol, Tomáš

The paper presents an approach to the semantic modelling and annotation of business processes and information resources, as it was designed within the FP7 ICT EU project SPIKE to support creation and maintenance of short-term business alliances and networked enterprises. A methodology for the development of the resource ontology, as a shareable knowledge model for semantic description of business processes, is proposed. Systematically collected user requirements, conceptual models implied by the selected implementation platform as well as available ontology resources and standards are employed in the ontology creation. The process of semantic annotation is described and illustrated using an example taken from a real application case.

Challenges Facing the Semantic Web and Social Software as Communication Technology Agents in E-Learning Environments

ERIC Educational Resources Information Center

Olaniran, Bolanle A.

2010-01-01

The semantic web describes the process whereby information content is made available for machine consumption. With increased reliance on information communication technologies, the semantic web promises effective and efficient information acquisition and dissemination of products and services in the global economy, in particular, e-learning.…

[Schizophrenia and semantic priming effects].

PubMed

Lecardeur, L; Giffard, B; Eustache, F; Dollfus, S

2006-01-01

This article is a review of studies using the semantic priming paradigm to assess the functioning of semantic memory in schizophrenic patients. Semantic priming describes the phenomenon of increasing the speed with which a string of letters (the target) is recognized as a word (lexical decision task) by presenting to the subject a semantically related word (the prime) prior to the appearance of the target word. This semantic priming is linked to both automatic and controlled processes depending on experimental conditions (stimulus onset asynchrony (SOA), percentage of related words and explicit memory instructions). Automatic process observed with short SOA, low related word percentage and instructions asking only to process the target, could be linked to the "automatic spreading activation" through the semantic network. Controlled processes involve "semantic matching" (the number of related and unrelated pairs influences the subjects decision) and "expectancy" (the prime leads the subject to generate an expectancy set of potential target to the prime). These processes can be observed whatever the SOA for the former and with long SOA for the later, but both with only high related word percentage and explicit memory instructions. Studies evaluating semantic priming effects in schizophrenia show conflicting results: schizophrenic patients can present hyperpriming (semantic priming effect is larger in patients than in controls), hypopriming (semantic priming effect is lower in patients than in controls) or equal semantic priming effects compared to control subjects. These results could be associated to a global impairment of controlled processes in schizophrenia, essentially to a dysfunction of semantic matching process. On the other hand, efficiency of semantic automatic spreading activation process is controversial. These discrepancies could be linked to the different experimental conditions used (duration of SOA, proportion of related pairs and instructions), which

Spatial Relation Predicates in Topographic Feature Semantics

USGS Publications Warehouse

Varanka, Dalia E.; Caro, Holly K.

2013-01-01

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

Semantic Preview Benefit during Reading

ERIC Educational Resources Information Center

Hohenstein, Sven; Kliegl, Reinhold

2014-01-01

Word features in parafoveal vision influence eye movements during reading. The question of whether readers extract semantic information from parafoveal words was studied in 3 experiments by using a gaze-contingent display change technique. Subjects read German sentences containing 1 of several preview words that were replaced by a target word…

An object-oriented design for automated navigation of semantic networks inside a medical data dictionary.

PubMed

Ruan, W; Bürkle, T; Dudeck, J

2000-01-01

In this paper we present a data dictionary server for the automated navigation of information sources. The underlying knowledge is represented within a medical data dictionary. The mapping between medical terms and information sources is based on a semantic network. The key aspect of implementing the dictionary server is how to represent the semantic network in a way that is easier to navigate and to operate, i.e. how to abstract the semantic network and to represent it in memory for various operations. This paper describes an object-oriented design based on Java that represents the semantic network in terms of a group of objects. A node and its relationships to its neighbors are encapsulated in one object. Based on such a representation model, several operations have been implemented. They comprise the extraction of parts of the semantic network which can be reached from a given node as well as finding all paths between a start node and a predefined destination node. This solution is independent of any given layout of the semantic structure. Therefore the module, called Giessen Data Dictionary Server can act independent of a specific clinical information system. The dictionary server will be used to present clinical information, e.g. treatment guidelines or drug information sources to the clinician in an appropriate working context. The server is invoked from clinical documentation applications which contain an infobutton. Automated navigation will guide the user to all the information relevant to her/his topic, which is currently available inside our closed clinical network.

Towards a Semantically-Enabled Control Strategy for Building Simulations: Integration of Semantic Technologies and Model Predictive Control

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

Delgoshaei, Parastoo; Austin, Mark A.; Pertzborn, Amanda J.

State-of-the-art building simulation control methods incorporate physical constraints into their mathematical models, but omit implicit constraints associated with policies of operation and dependency relationships among rules representing those constraints. To overcome these shortcomings, there is a recent trend in enabling the control strategies with inference-based rule checking capabilities. One solution is to exploit semantic web technologies in building simulation control. Such approaches provide the tools for semantic modeling of domains, and the ability to deduce new information based on the models through use of Description Logic (DL). In a step toward enabling this capability, this paper presents a cross-disciplinary data-drivenmore » control strategy for building energy management simulation that integrates semantic modeling and formal rule checking mechanisms into a Model Predictive Control (MPC) formulation. The results show that MPC provides superior levels of performance when initial conditions and inputs are derived from inference-based rules.« less

Verbal and non-verbal semantic impairment: From fluent primary progressive aphasia to semantic dementia

PubMed Central

Senaha, Mirna Lie Hosogi; Caramelli, Paulo; Porto, Claudia Sellitto; Nitrini, Ricardo

2007-01-01

Selective disturbances of semantic memory have attracted the interest of many investigators and the question of the existence of single or multiple semantic systems remains a very controversial theme in the literature. Objectives To discuss the question of multiple semantic systems based on a longitudinal study of a patient who presented semantic dementia from fluent primary progressive aphasia. Methods A 66 year-old woman with selective impairment of semantic memory was examined on two occasions, undergoing neuropsychological and language evaluations, the results of which were compared to those of three paired control individuals. Results In the first evaluation, physical examination was normal and the score on the Mini-Mental State Examination was 26. Language evaluation revealed fluent speech, anomia, disturbance in word comprehension, preservation of the syntactic and phonological aspects of the language, besides surface dyslexia and dysgraphia. Autobiographical and episodic memories were relatively preserved. In semantic memory tests, the following dissociation was found: disturbance of verbal semantic memory with preservation of non-verbal semantic memory. Magnetic resonance of the brain revealed marked atrophy of the left anterior temporal lobe. After 14 months, the difficulties in verbal semantic memory had become more severe and the semantic disturbance, limited initially to the linguistic sphere, had worsened to involve non-verbal domains. Conclusions Given the dissociation found in the first examination, we believe there is sufficient clinical evidence to refute the existence of a unitary semantic system. PMID:29213389

Syntactic processing in the absence of awareness and semantics.

PubMed

Hung, Shao-Min; Hsieh, Po-Jang

2015-10-01

The classical view that multistep rule-based operations require consciousness has recently been challenged by findings that both multiword semantic processing and multistep arithmetic equations can be processed unconsciously. It remains unclear, however, whether pure rule-based cognitive processes can occur unconsciously in the absence of semantics. Here, after presenting 2 words consciously, we suppressed the third with continuous flash suppression. First, we showed that the third word in the subject-verb-verb format (syntactically incongruent) broke suppression significantly faster than the third word in the subject-verb-object format (syntactically congruent). Crucially, the same effect was observed even with sentences composed of pseudowords (pseudo subject-verb-adjective vs. pseudo subject-verb-object) without any semantic information. This is the first study to show that syntactic congruency can be processed unconsciously in the complete absence of semantics. Our findings illustrate how abstract rule-based processing (e.g., syntactic categories) can occur in the absence of visual awareness, even when deprived of semantics. (c) 2015 APA, all rights reserved).

The accessibility of semantic knowledge for odours that can and cannot be named.

PubMed

Stevenson, Richard J; Mahmut, Mehmet K

2013-01-01

When faces, objects, or voices are encountered, naming lapses can occur, but this does not preclude knowing other specific semantic information about the nameless thing. In the experiments reported here, we examined whether this is also the case for odours, using a procedure based upon the Pyramid and Palm Trees test. In Experiment 1, participants were presented with a target odour, then two pictures, and had to pick the picture semantically associated with the target. In Experiment 2, participants were presented with a target odour, then two test odours, and again had to pick the semantically associated test stimulus. In each experiment, other tests followed, including a parallel verbal-based test, an odour-naming test, and various ratings. Neither experiment found any evidence of specific semantic knowledge about a target odour, unless the target odour name (Experiment 1) or all of the odour names (Experiment 2) were known. Additional tests suggested that these effects were independent of odour familiarity and similarity. We suggest that the absence of specific semantic information in the absence of a name may reflect poor connectivity between olfactory perceptual and semantic memory systems.

Exploring semantic and phonological picture-word priming in adults who stutter using event-related potentials

PubMed Central

Maxfield, Nathan D.; Pizon-Moore, Angela A.; Frisch, Stefan A.; Constantine, Joseph L.

2011-01-01

Objective Our aim was to investigate how semantic and phonological information is processed in adults who stutter (AWS) preparing to name pictures, following-up a report that event-related potentials (ERPs) in AWS evidenced atypical semantic picture-word priming (Maxfield et al., 2010). Methods Fourteen AWS and 14 typically-fluent adults (TFA) participated. Pictures, named at a delay, were followed by probe words. Design elements not used in Maxfield et al. (2010) let us evaluate both phonological and semantic picture-word priming. Results TFA evidenced typical priming effects in probe-elicited ERPs. AWS evidenced diminished Semantic priming, and reverse Phonological N400 priming. Conclusions Results point to atypical processing of semantic and phonological information in AWS. Discussion considers whether AWS ERP effects reflect unstable activation of target label semantic and phonological representations, strategic inhibition of target label phonological neighbors, and/or phonological label-probe competition. Significance Results raise questions about how mechanisms that regulate activation spreading operate in AWS. PMID:22055837

Combining Temporal and Spectral Information with Spatial Mapping to Identify Differences between Phonological and Semantic Networks: A Magnetoencephalographic Approach

PubMed Central

McNab, Fiona; Hillebrand, Arjan; Swithenby, Stephen J.; Rippon, Gina

2012-01-01

Early, lesion-based models of language processing suggested that semantic and phonological processes are associated with distinct temporal and parietal regions respectively, with frontal areas more indirectly involved. Contemporary spatial brain mapping techniques have not supported such clear-cut segregation, with strong evidence of activation in left temporal areas by both processes and disputed evidence of involvement of frontal areas in both processes. We suggest that combining spatial information with temporal and spectral data may allow a closer scrutiny of the differential involvement of closely overlapping cortical areas in language processing. Using beamforming techniques to analyze magnetoencephalography data, we localized the neuronal substrates underlying primed responses to nouns requiring either phonological or semantic processing, and examined the associated measures of time and frequency in those areas where activation was common to both tasks. Power changes in the beta (14–30 Hz) and gamma (30–50 Hz) frequency bands were analyzed in pre-selected time windows of 350–550 and 500–700 ms In left temporal regions, both tasks elicited power changes in the same time window (350–550 ms), but with different spectral characteristics, low beta (14–20 Hz) for the phonological task and high beta (20–30 Hz) for the semantic task. In frontal areas (BA10), both tasks elicited power changes in the gamma band (30–50 Hz), but in different time windows, 500–700 ms for the phonological task and 350–550 ms for the semantic task. In the left inferior parietal area (BA40), both tasks elicited changes in the 20–30 Hz beta frequency band but in different time windows, 350–550 ms for the phonological task and 500–700 ms for the semantic task. Our findings suggest that, where spatial measures may indicate overlapping areas of involvement, additional beamforming techniques can demonstrate differential activation in time and

Combining Temporal and Spectral Information with Spatial Mapping to Identify Differences between Phonological and Semantic Networks: A Magnetoencephalographic Approach.

PubMed

McNab, Fiona; Hillebrand, Arjan; Swithenby, Stephen J; Rippon, Gina

2012-01-01

Early, lesion-based models of language processing suggested that semantic and phonological processes are associated with distinct temporal and parietal regions respectively, with frontal areas more indirectly involved. Contemporary spatial brain mapping techniques have not supported such clear-cut segregation, with strong evidence of activation in left temporal areas by both processes and disputed evidence of involvement of frontal areas in both processes. We suggest that combining spatial information with temporal and spectral data may allow a closer scrutiny of the differential involvement of closely overlapping cortical areas in language processing. Using beamforming techniques to analyze magnetoencephalography data, we localized the neuronal substrates underlying primed responses to nouns requiring either phonological or semantic processing, and examined the associated measures of time and frequency in those areas where activation was common to both tasks. Power changes in the beta (14-30 Hz) and gamma (30-50 Hz) frequency bands were analyzed in pre-selected time windows of 350-550 and 500-700 ms In left temporal regions, both tasks elicited power changes in the same time window (350-550 ms), but with different spectral characteristics, low beta (14-20 Hz) for the phonological task and high beta (20-30 Hz) for the semantic task. In frontal areas (BA10), both tasks elicited power changes in the gamma band (30-50 Hz), but in different time windows, 500-700 ms for the phonological task and 350-550 ms for the semantic task. In the left inferior parietal area (BA40), both tasks elicited changes in the 20-30 Hz beta frequency band but in different time windows, 350-550 ms for the phonological task and 500-700 ms for the semantic task. Our findings suggest that, where spatial measures may indicate overlapping areas of involvement, additional beamforming techniques can demonstrate differential activation in time and frequency domains.

Evidence of semantic processing impairments in behavioural variant frontotemporal dementia and Parkinson's disease.

PubMed

Cousins, Katheryn A Q; Grossman, Murray

2017-12-01

Category-specific impairments caused by brain damage can provide important insights into how semantic concepts are organized in the brain. Recent research has demonstrated that disease to sensory and motor cortices can impair perceptual feature knowledge important to the representation of semantic concepts. This evidence supports the grounded cognition theory of semantics, the view that lexical knowledge is partially grounded in perceptual experience and that sensory and motor regions support semantic representations. Less well understood, however, is how heteromodal semantic hubs work to integrate and process semantic information. Although the majority of semantic research to date has focused on how sensory cortical areas are important for the representation of semantic features, new research explores how semantic memory is affected by neurodegeneration in regions important for semantic processing. Here, we review studies that demonstrate impairments to abstract noun knowledge in behavioural variant frontotemporal degeneration (bvFTD) and to action verb knowledge in Parkinson's disease, and discuss how these deficits relate to disease of the semantic selection network. Findings demonstrate that semantic selection processes are supported by the left inferior frontal gyrus (LIFG) and basal ganglia, and that disease to these regions in bvFTD and Parkinson's disease can lead to categorical impairments for abstract nouns and action verbs, respectively.

Semantic Neighborhood Effects for Abstract versus Concrete Words

PubMed Central

Danguecan, Ashley N.; Buchanan, Lori

2016-01-01

Studies show that semantic effects may be task-specific, and thus, that semantic representations are flexible and dynamic. Such findings are critical to the development of a comprehensive theory of semantic processing in visual word recognition, which should arguably account for how semantic effects may vary by task. It has been suggested that semantic effects are more directly examined using tasks that explicitly require meaning processing relative to those for which meaning processing is not necessary (e.g., lexical decision task). The purpose of the present study was to chart the processing of concrete versus abstract words in the context of a global co-occurrence variable, semantic neighborhood density (SND), by comparing word recognition response times (RTs) across four tasks varying in explicit semantic demands: standard lexical decision task (with non-pronounceable non-words), go/no-go lexical decision task (with pronounceable non-words), progressive demasking task, and sentence relatedness task. The same experimental stimulus set was used across experiments and consisted of 44 concrete and 44 abstract words, with half of these being low SND, and half being high SND. In this way, concreteness and SND were manipulated in a factorial design using a number of visual word recognition tasks. A consistent RT pattern emerged across tasks, in which SND effects were found for abstract (but not necessarily concrete) words. Ultimately, these findings highlight the importance of studying interactive effects in word recognition, and suggest that linguistic associative information is particularly important for abstract words. PMID:27458422

Implicit Word Learning Benefits from Semantic Richness: Electrophysiological and Behavioral Evidence

ERIC Educational Resources Information Center

Rabovsky, Milena; Sommer, Werner; Abdel Rahman, Rasha

2012-01-01

Words differ considerably in the amount of associated semantic information. Despite the crucial role of meaning in language, it is still unclear whether and how this variability modulates language learning. Here, we provide initial evidence demonstrating that implicit learning in repetition priming is influenced by the amount of semantic features…

Individual Differences in a Spatial-Semantic Virtual Environment.

ERIC Educational Resources Information Center

Chen, Chaomei

2000-01-01

Presents two empirical case studies concerning the role of individual differences in searching through a spatial-semantic virtual environment. Discusses information visualization in information systems; cognitive factors, including associative memory, spatial ability, and visual memory; user satisfaction; and cognitive abilities and search…

High Performance Semantic Factoring of Giga-Scale Semantic Graph Databases

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

Joslyn, Cliff A.; Adolf, Robert D.; Al-Saffar, Sinan

2010-10-04

As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to bring high performance computational resources to bear on their analysis, interpretation, and visualization, especially with respect to their innate semantic structure. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multithreaded architecture of the Cray XMT platform, conventional clusters, and large data stores. In this paper we describe that architecture, and present the results of our deployingmore » that for the analysis of the Billion Triple dataset with respect to its semantic factors.« less

SAS- Semantic Annotation Service for Geoscience resources on the web

NASA Astrophysics Data System (ADS)

Elag, M.; Kumar, P.; Marini, L.; Li, R.; Jiang, P.

2015-12-01

There is a growing need for increased integration across the data and model resources that are disseminated on the web to advance their reuse across different earth science applications. Meaningful reuse of resources requires semantic metadata to realize the semantic web vision for allowing pragmatic linkage and integration among resources. Semantic metadata associates standard metadata with resources to turn them into semantically-enabled resources on the web. However, the lack of a common standardized metadata framework as well as the uncoordinated use of metadata fields across different geo-information systems, has led to a situation in which standards and related Standard Names abound. To address this need, we have designed SAS to provide a bridge between the core ontologies required to annotate resources and information systems in order to enable queries and analysis over annotation from a single environment (web). SAS is one of the services that are provided by the Geosematnic framework, which is a decentralized semantic framework to support the integration between models and data and allow semantically heterogeneous to interact with minimum human intervention. Here we present the design of SAS and demonstrate its application for annotating data and models. First we describe how predicates and their attributes are extracted from standards and ingested in the knowledge-base of the Geosemantic framework. Then we illustrate the application of SAS in annotating data managed by SEAD and annotating simulation models that have web interface. SAS is a step in a broader approach to raise the quality of geoscience data and models that are published on the web and allow users to better search, access, and use of the existing resources based on standard vocabularies that are encoded and published using semantic technologies.

Enemies and friends in the neighborhood: orthographic similarity effects in semantic categorization.

PubMed

Pecher, Diane; Zeelenberg, René; Wagenmakers, Eric-Jan

2005-01-01

Studies investigating orthographic similarity effects in semantic tasks have produced inconsistent results. The authors investigated orthographic similarity effects in animacy decision and in contrast with previous studies, they took semantic congruency into account. In Experiments 1 and 2, performance to a target (cat) was better if a previously studied neighbor (rat) was congruent (i.e., belonged to the same animate-inanimate category) than it was if it was incongruent (e.g., mat). In Experiments 3 and 4, performance was better for targets with more preexisting congruent neighbors than for targets with more preexisting incongruent neighbors. These results demonstrate that orthographic similarity effects in semantic categorization are conditional on semantic congruency. This strongly suggests that semantic information becomes available before orthographic processing has been completed. 2005 APA

The Analysis of RDF Semantic Data Storage Optimization in Large Data Era

NASA Astrophysics Data System (ADS)

He, Dandan; Wang, Lijuan; Wang, Can

2018-03-01

With the continuous development of information technology and network technology in China, the Internet has also ushered in the era of large data. In order to obtain the effective acquisition of information in the era of large data, it is necessary to optimize the existing RDF semantic data storage and realize the effective query of various data. This paper discusses the storage optimization of RDF semantic data under large data.

Episodic and semantic memory in children with mesial temporal sclerosis.

PubMed

Rzezak, Patricia; Guimarães, Catarina; Fuentes, Daniel; Guerreiro, Marilisa M; Valente, Kette Dualibi Ramos

2011-07-01

The aim of this study was to analyze semantic and episodic memory deficits in children with mesial temporal sclerosis (MTS) and their correlation with clinical epilepsy variables. For this purpose, 19 consecutive children and adolescents with MTS (8 to 16 years old) were evaluated and their performance on five episodic memory tests (short- and long-term memory and learning) and four semantic memory tests was compared with that of 28 healthy volunteers. Patients performed worse on tests of immediate and delayed verbal episodic memory, visual episodic memory, verbal and visual learning, mental scanning for semantic clues, object naming, word definition, and repetition of sentences. Clinical variables such as early age at seizure onset, severity of epilepsy, and polytherapy impaired distinct types of memory. These data confirm that children with MTS have episodic memory deficits and add new information on semantic memory. The data also demonstrate that clinical variables contribute differently to episodic and semantic memory performance. Copyright © 2011 Elsevier Inc. All rights reserved.

Neural Basis of Semantic and Syntactic Interference in Sentence Comprehension

PubMed Central

Glaser, Yi G.; Martin, Randi C.; Van Dyke, Julie A.; Hamilton, A. Cris; Tan, Yingying

2013-01-01

According to the cue-based parsing approach (Lewis, Vasishth, & Van Dyke, 2006), sentence comprehension difficulty derives from interference from material that partially matches syntactic and semantic retrieval cues. In a 2 (low vs. high semantic interference) × 2 (low vs. high syntactic interference) fMRI study, greater activation was observed in left BA 44/45 for high versus low syntactic interference conditions following sentences and in BA 45/47 for high versus low semantic interference following comprehension questions. A conjunction analysis showed BA45 associated with both types of interference, while BA47 was associated with only semantic interference. Greater activation was also observed in the left STG in the high interference conditions. Importantly, the results for the LIFG could not be attributed to greater working memory capacity demands for high interference conditions. The results favor a fractionation of LIFG wherein BA45 is associated with post-retrieval selection and BA47 with controlled retrieval of semantic information. PMID:23933471

A Semantic Constraint on Syntactic Parsing.

ERIC Educational Resources Information Center

Crain, Stephen; Coker, Pamela L.

This research examines how semantic information influences syntactic parsing decisions during sentence processing. In the first experiment, subjects were presented lexical strings having syntactically identical surface structures but with two possible underlying structures: "The children taught by the Berlitz method," and "The…

Controlled semantic cognition relies upon dynamic and flexible interactions between the executive 'semantic control' and hub-and-spoke 'semantic representation' systems.

PubMed

Chiou, Rocco; Humphreys, Gina F; Jung, JeYoung; Lambon Ralph, Matthew A

2018-06-01

Built upon a wealth of neuroimaging, neurostimulation, and neuropsychology data, a recent proposal set forth a framework termed controlled semantic cognition (CSC) to account for how the brain underpins the ability to flexibly use semantic knowledge (Lambon Ralph et al., 2017; Nature Reviews Neuroscience). In CSC, the 'semantic control' system, underpinned predominantly by the prefrontal cortex, dynamically monitors and modulates the 'semantic representation' system that consists of a 'hub' (anterior temporal lobe, ATL) and multiple 'spokes' (modality-specific areas). CSC predicts that unfamiliar and exacting semantic tasks should intensify communication between the 'control' and 'representation' systems, relative to familiar and less taxing tasks. In the present study, we used functional magnetic resonance imaging (fMRI) to test this hypothesis. Participants paired unrelated concepts by canonical colours (a less accustomed task - e.g., pairing ketchup with fire-extinguishers due to both being red) or paired well-related concepts by semantic relationship (a typical task - e.g., ketchup is related to mustard). We found the 'control' system was more engaged by atypical than typical pairing. While both tasks activated the ATL 'hub', colour pairing additionally involved occipitotemporal 'spoke' regions abutting areas of hue perception. Furthermore, we uncovered a gradient along the ventral temporal cortex, transitioning from the caudal 'spoke' zones preferring canonical colour processing to the rostral 'hub' zones preferring semantic relationship. Functional connectivity also differed between the tasks: Compared with semantic pairing, colour pairing relied more upon the inferior frontal gyrus, a key node of the control system, driving enhanced connectivity with occipitotemporal 'spoke'. Together, our findings characterise the interaction within the neural architecture of semantic cognition - the control system dynamically heightens its connectivity with relevant

Semantic Interoperability of Health Risk Assessments