Semantic integration of medication data into the EHOP Clinical Data Warehouse.

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Delamarre, Denis; Bouzille, Guillaume; Dalleau, Kevin; Courtel, Denis; Cuggia, Marc

2015-01-01

Reusing medication data is crucial for many medical research domains. Semantic integration of such data in clinical data warehouse (CDW) is quite challenging. Our objective was to develop a reliable and scalable method for integrating prescription data into EHOP (a French CDW). PN13/PHAST was used as the semantic interoperability standard during the ETL process, and to store the prescriptions as documents in the CDW. Theriaque was used as a drug knowledge database (DKDB), to annotate the prescription dataset with the finest granularity, and to provide semantic capabilities to the EHOP query workbench. the system was evaluated on a clinical data set. Depending on the use case, the precision ranged from 52% to 100%, Recall was always 100%. interoperability standards and DKDB, document approach, and the finest granularity approach are the key factors for successful drug data integration in CDW.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

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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.

Uncertainty modeling process for semantic technology

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Rommel N. Carvalho

2016-08-01

Full Text Available The ubiquity of uncertainty across application domains generates a need for principled support for uncertainty management in semantically aware systems. A probabilistic ontology provides constructs for representing uncertainty in domain ontologies. While the literature has been growing on formalisms for representing uncertainty in ontologies, there remains little guidance in the knowledge engineering literature for how to design probabilistic ontologies. To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST, a new methodology for modeling probabilistic ontologies. To explain how the methodology works and to verify that it can be applied to different scenarios, this paper describes step-by-step the construction of a proof-of-concept probabilistic ontology. The resulting domain model can be used to support identification of fraud in public procurements in Brazil. While the case study illustrates the development of a probabilistic ontology in the PR-OWL probabilistic ontology language, the methodology is applicable to any ontology formalism that properly integrates uncertainty with domain semantics.

[An effect of semantic satiation in conceptual processing].

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Takashi, Shimokido

2007-12-01

This study examined whether semantic satiation effects for a picture exemplar differ from a word exemplar. If massive repetition of the category name leads to an inhibition of conceptual processing, then semantic satiation effects would be found in both the word and picture exemplar conditions. However, if the repetition leads to an inhibition of lexical processing, then effects would be found for the word exemplar but not the picture exemplar. To examine these hypotheses, 48 college students were asked to judge whether a target pair of exemplars belonged to the same named category. The results showed that semantic satiation effects were found equally in both exemplar conditions. Moreover, the picture-superiority effect was intact regardless of the prime repetitions. The possibility was discussed that word and picture exemplars are integrated into an abstract and amodal conceptual unit; hence category judgment was affected by the satiation effect.

Cross-modal integration of lexical-semantic features during word processing: evidence from oscillatory dynamics during EEG.

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Markus J van Ackeren

Full Text Available In recent years, numerous studies have provided converging evidence that word meaning is partially stored in modality-specific cortical networks. However, little is known about the mechanisms supporting the integration of this distributed semantic content into coherent conceptual representations. In the current study we aimed to address this issue by using EEG to look at the spatial and temporal dynamics of feature integration during word comprehension. Specifically, participants were presented with two modality-specific features (i.e., visual or auditory features such as silver and loud and asked to verify whether these two features were compatible with a subsequently presented target word (e.g., WHISTLE. Each pair of features described properties from either the same modality (e.g., silver, tiny  =  visual features or different modalities (e.g., silver, loud  =  visual, auditory. Behavioral and EEG data were collected. The results show that verifying features that are putatively represented in the same modality-specific network is faster than verifying features across modalities. At the neural level, integrating features across modalities induces sustained oscillatory activity around the theta range (4-6 Hz in left anterior temporal lobe (ATL, a putative hub for integrating distributed semantic content. In addition, enhanced long-range network interactions in the theta range were seen between left ATL and a widespread cortical network. These results suggest that oscillatory dynamics in the theta range could be involved in integrating multimodal semantic content by creating transient functional networks linking distributed modality-specific networks and multimodal semantic hubs such as left ATL.

Semantic Business Process Modeling

OpenAIRE

Markovic, Ivan

2010-01-01

This book presents a process-oriented business modeling framework based on semantic technologies. The framework consists of modeling languages, methods, and tools that allow for semantic modeling of business motivation, business policies and rules, and business processes. Quality of the proposed modeling framework is evaluated based on the modeling content of SAP Solution Composer and several real-world business scenarios.

What do information reuse and automated processing require in engineering design? Semantic process

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Ossi Nykänen

2011-12-01

Full Text Available Purpose: The purpose of this study is to characterize, analyze, and demonstrate machine-understandable semantic process for validating, integrating, and processing technical design information. This establishes both a vision and tools for information reuse and semi-automatic processing in engineering design projects, including virtual machine laboratory applications with generated components.Design/methodology/approach: The process model has been developed iteratively in terms of action research, constrained by the existing technical design practices and assumptions (design documents, expert feedback, available technologies (pre-studies and experiments with scripting and pipeline tools, benchmarking with other process models and methods (notably the RUP and DITA, and formal requirements (computability and the critical information paths for the generated applications. In practice, the work includes both quantitative and qualitative components.Findings: Technical design processes may be greatly enhanced in terms of semantic process thinking, by enriching design information, and automating information validation and transformation tasks. Contemporary design information, however, is mainly intended for human consumption, and needs to be explicitly enriched with the currently missing data and interfaces. In practice, this may require acknowledging the role of technical information or knowledge engineer, to lead the development of the semantic design information process in a design organization. There is also a trade-off between machine-readability and system complexity that needs to be studied further, both empirically and in theory.Research limitations/implications: The conceptualization of the semantic process is essentially an abstraction based on the idea of progressive design. While this effectively allows implementing semantic processes with, e.g., pipeline technologies, the abstraction is valid only when technical design is organized into

Semantic multimedia analysis and processing

CERN Document Server

Spyrou, Evaggelos; Mylonas, Phivos

2014-01-01

Broad in scope, Semantic Multimedia Analysis and Processing provides a complete reference of techniques, algorithms, and solutions for the design and the implementation of contemporary multimedia systems. Offering a balanced, global look at the latest advances in semantic indexing, retrieval, analysis, and processing of multimedia, the book features the contributions of renowned researchers from around the world. Its contents are based on four fundamental thematic pillars: 1) information and content retrieval, 2) semantic knowledge exploitation paradigms, 3) multimedia personalization, and 4)

Neural changes associated with semantic processing in healthy aging despite intact behavioral performance.

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Lacombe, Jacinthe; Jolicoeur, Pierre; Grimault, Stephan; Pineault, Jessica; Joubert, Sven

2015-10-01

Semantic memory recruits an extensive neural network including the left inferior prefrontal cortex (IPC) and the left temporoparietal region, which are involved in semantic control processes, as well as the anterior temporal lobe region (ATL) which is considered to be involved in processing semantic information at a central level. However, little is known about the underlying neuronal integrity of the semantic network in normal aging. Young and older healthy adults carried out a semantic judgment task while their cortical activity was recorded using magnetoencephalography (MEG). Despite equivalent behavioral performance, young adults activated the left IPC to a greater extent than older adults, while the latter group recruited the temporoparietal region bilaterally and the left ATL to a greater extent than younger adults. Results indicate that significant neuronal changes occur in normal aging, mainly in regions underlying semantic control processes, despite an apparent stability in performance at the behavioral level. Copyright © 2015 Elsevier Inc. All rights reserved.

Domain XML semantic integration based on extraction rules and ontology mapping

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Huayu LI

2016-08-01

Full Text Available A plenty of XML documents exist in petroleum engineering field, but traditional XML integration solution can’t provide semantic query, which leads to low data use efficiency. In light of WeXML(oil&gas well XML data semantic integration and query requirement, this paper proposes a semantic integration method based on extraction rules and ontology mapping. The method firstly defines a series of extraction rules with which elements and properties of WeXML Schema are mapped to classes and properties in WeOWL ontology, respectively; secondly, an algorithm is used to transform WeXML documents into WeOWL instances. Because WeOWL provides limited semantics, ontology mappings between two ontologies are then built to explain class and property of global ontology with terms of WeOWL, and semantic query based on global domain concepts model is provided. By constructing a WeXML data semantic integration prototype system, the proposed transformational rule, the transfer algorithm and the mapping rule are tested.

Incorporating Semantic Knowledge into Dynamic Data Processing for Smart Power Grids

Energy Technology Data Exchange (ETDEWEB)

Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor

2012-11-15

Semantic Web allows us to model and query time-invariant or slowly evolving knowledge using ontologies. Emerging applications in Cyber Physical Systems such as Smart Power Grids that require continuous information monitoring and integration present novel opportunities and challenges for Semantic Web technologies. Semantic Web is promising to model diverse Smart Grid domain knowledge for enhanced situation awareness and response by multi-disciplinary participants. However, current technology does pose a performance overhead for dynamic analysis of sensor measurements. In this paper, we combine semantic web and complex event processing for stream based semantic querying. We illustrate its adoption in the USC Campus Micro-Grid for detecting and enacting dynamic response strategies to peak power situations by diverse user roles. We also describe the semantic ontology and event query model that supports this. Further, we introduce and evaluate caching techniques to improve the response time for semantic event queries to meet our application needs and enable sustainable energy management.

Semantic word category processing in semantic dementia and posterior cortical atrophy.

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Shebani, Zubaida; Patterson, Karalyn; Nestor, Peter J; Diaz-de-Grenu, Lara Z; Dawson, Kate; Pulvermüller, Friedemann

2017-08-01

There is general agreement that perisylvian language cortex plays a major role in lexical and semantic processing; but the contribution of additional, more widespread, brain areas in the processing of different semantic word categories remains controversial. We investigated word processing in two groups of patients whose neurodegenerative diseases preferentially affect specific parts of the brain, to determine whether their performance would vary as a function of semantic categories proposed to recruit those brain regions. Cohorts with (i) Semantic Dementia (SD), who have anterior temporal-lobe atrophy, and (ii) Posterior Cortical Atrophy (PCA), who have predominantly parieto-occipital atrophy, performed a lexical decision test on words from five different lexico-semantic categories: colour (e.g., yellow), form (oval), number (seven), spatial prepositions (under) and function words (also). Sets of pseudo-word foils matched the target words in length and bi-/tri-gram frequency. Word-frequency was matched between the two visual word categories (colour and form) and across the three other categories (number, prepositions, and function words). Age-matched healthy individuals served as controls. Although broad word processing deficits were apparent in both patient groups, the deficit was strongest for colour words in SD and for spatial prepositions in PCA. The patterns of performance on the lexical decision task demonstrate (a) general lexicosemantic processing deficits in both groups, though more prominent in SD than in PCA, and (b) differential involvement of anterior-temporal and posterior-parietal cortex in the processing of specific semantic categories of words. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Embedding Metadata and Other Semantics in Word Processing Documents

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Peter Sefton

2009-10-01

Full Text Available This paper describes a technique for embedding document metadata, and potentially other semantic references inline in word processing documents, which the authors have implemented with the help of a software development team. Several assumptions underly the approach; It must be available across computing platforms and work with both Microsoft Word (because of its user base and OpenOffice.org (because of its free availability. Further the application needs to be acceptable to and usable by users, so the initial implementation covers only small number of features, which will only be extended after user-testing. Within these constraints the system provides a mechanism for encoding not only simple metadata, but for inferring hierarchical relationships between metadata elements from a ‘flat’ word processing file.The paper includes links to open source code implementing the techniques as part of a broader suite of tools for academic writing. This addresses tools and software, semantic web and data curation, integrating curation into research workflows and will provide a platform for integrating work on ontologies, vocabularies and folksonomies into word processing tools.

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

Science.gov (United States)

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

Exploring the role of the posterior middle temporal gyrus in semantic cognition: Integration of anterior temporal lobe with executive processes.

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Davey, James; Thompson, Hannah E; Hallam, Glyn; Karapanagiotidis, Theodoros; Murphy, Charlotte; De Caso, Irene; Krieger-Redwood, Katya; Bernhardt, Boris C; Smallwood, Jonathan; Jefferies, Elizabeth

2016-08-15

Making sense of the world around us depends upon selectively retrieving information relevant to our current goal or context. However, it is unclear whether selective semantic retrieval relies exclusively on general control mechanisms recruited in demanding non-semantic tasks, or instead on systems specialised for the control of meaning. One hypothesis is that the left posterior middle temporal gyrus (pMTG) is important in the controlled retrieval of semantic (not non-semantic) information; however this view remains controversial since a parallel literature links this site to event and relational semantics. In a functional neuroimaging study, we demonstrated that an area of pMTG implicated in semantic control by a recent meta-analysis was activated in a conjunction of (i) semantic association over size judgements and (ii) action over colour feature matching. Under these circumstances the same region showed functional coupling with the inferior frontal gyrus - another crucial site for semantic control. Structural and functional connectivity analyses demonstrated that this site is at the nexus of networks recruited in automatic semantic processing (the default mode network) and executively demanding tasks (the multiple-demand network). Moreover, in both task and task-free contexts, pMTG exhibited functional properties that were more similar to ventral parts of inferior frontal cortex, implicated in controlled semantic retrieval, than more dorsal inferior frontal sulcus, implicated in domain-general control. Finally, the pMTG region was functionally correlated at rest with other regions implicated in control-demanding semantic tasks, including inferior frontal gyrus and intraparietal sulcus. We suggest that pMTG may play a crucial role within a large-scale network that allows the integration of automatic retrieval in the default mode network with executively-demanding goal-oriented cognition, and that this could support our ability to understand actions and non

Dynamic information processing states revealed through neurocognitive models of object semantics

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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

Age-related changes in ERP components of semantic and syntactic processing in a verb final language

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Jee Eun Sung

2014-04-01

Both syntactic and semantic violations elicited negativity effects at 300-500ms time window, and the negativity effects were slightly attenuated in the elderly group. The results suggested that Korean speakers may process a syntactic component of a case marker under the semantic frame integration, eliciting the negativity effects associated with semantic violations. Elderly adults showed attenuated effects compared to the young group, indicating age-related changes emerged during real-time sentence processing.

Mixing positive and negative valence: Affective-semantic integration of bivalent words.

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Kuhlmann, Michael; Hofmann, Markus J; Briesemeister, Benny B; Jacobs, Arthur M

2016-08-05

Single words have affective and aesthetic properties that influence their processing. Here we investigated the processing of a special case of word stimuli that are extremely difficult to evaluate, bivalent noun-noun-compounds (NNCs), i.e. novel words that mix a positive and negative noun, e.g. 'Bombensex' (bomb-sex). In a functional magnetic resonance imaging (fMRI) experiment we compared their processing with easier-to-evaluate non-bivalent NNCs in a valence decision task (VDT). Bivalent NNCs produced longer reaction times and elicited greater activation in the left inferior frontal gyrus (LIFG) than non-bivalent words, especially in contrast to words of negative valence. We attribute this effect to a LIFG-grounded process of semantic integration that requires greater effort for processing converse information, supporting the notion of a valence representation based on associations in semantic networks.

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

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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.

Semantic Complex Event Processing over End-to-End Data Flows

Energy Technology Data Exchange (ETDEWEB)

Zhou, Qunzhi [University of Southern California; Simmhan, Yogesh; Prasanna, Viktor K.

2012-04-01

Emerging Complex Event Processing (CEP) applications in cyber physical systems like SmartPower Grids present novel challenges for end-to-end analysis over events, flowing from heterogeneous information sources to persistent knowledge repositories. CEP for these applications must support two distinctive features - easy specification patterns over diverse information streams, and integrated pattern detection over realtime and historical events. Existing work on CEP has been limited to relational query patterns, and engines that match events arriving after the query has been registered. We propose SCEPter, a semantic complex event processing framework which uniformly processes queries over continuous and archived events. SCEPteris built around an existing CEP engine with innovative support for semantic event pattern specification and allows their seamless detection over past, present and future events. Specifically, we describe a unified semantic query model that can operate over data flowing through event streams to event repositories. Compile-time and runtime semantic patterns are distinguished and addressed separately for efficiency. Query rewriting is examined and analyzed in the context of temporal boundaries that exist between event streams and their repository to avoid duplicate or missing results. The design and prototype implementation of SCEPterare analyzed using latency and throughput metrics for scenarios from the Smart Grid domain.

A SURVEY ON OPTIMIZATION APPROACHES TO SEMANTIC SERVICE DISCOVERY TOWARDS AN INTEGRATED SOLUTION

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Chellammal Surianarayanan

2012-07-01

Full Text Available The process of semantic service discovery using an ontology reasoner such as Pellet is time consuming. This restricts the usage of web services in real time applications having dynamic composition requirements. As performance of semantic service discovery is crucial in service composition, it should be optimized. Various optimization methods are being proposed to improve the performance of semantic discovery. In this work, we investigate the existing optimization methods and broadly classify optimization mechanisms into two categories, namely optimization by efficient reasoning and optimization by efficient matching. Optimization by efficient matching is further classified into subcategories such as optimization by clustering, optimization by inverted indexing, optimization by caching, optimization by hybrid methods, optimization by efficient data structures and optimization by efficient matching algorithms. With a detailed study of different methods, an integrated optimization infrastructure along with matching method has been proposed to improve the performance of semantic matching component. To achieve better optimization the proposed method integrates the effects of caching, clustering and indexing. Theoretical aspects of performance evaluation of the proposed method are discussed.

[Electrophysiological bases of semantic processing of objects].

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Kahlaoui, Karima; Baccino, Thierry; Joanette, Yves; Magnié, Marie-Noële

2007-02-01

How pictures and words are stored and processed in the human brain constitute a long-standing question in cognitive psychology. Behavioral studies have yielded a large amount of data addressing this issue. Generally speaking, these data show that there are some interactions between the semantic processing of pictures and words. However, behavioral methods can provide only limited insight into certain findings. Fortunately, Event-Related Potential (ERP) provides on-line cues about the temporal nature of cognitive processes and contributes to the exploration of their neural substrates. ERPs have been used in order to better understand semantic processing of words and pictures. The main objective of this article is to offer an overview of the electrophysiologic bases of semantic processing of words and pictures. Studies presented in this article showed that the processing of words is associated with an N 400 component, whereas pictures elicited both N 300 and N 400 components. Topographical analysis of the N 400 distribution over the scalp is compatible with the idea that both image-mediated concrete words and pictures access an amodal semantic system. However, given the distinctive N 300 patterns, observed only during picture processing, it appears that picture and word processing rely upon distinct neuronal networks, even if they end up activating more or less similar semantic representations.

Semantic integration to identify overlapping functional modules in protein interaction networks

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Ramanathan Murali

2007-07-01

Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

Graph-Based Semantic Web Service Composition for Healthcare Data Integration.

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Arch-Int, Ngamnij; Arch-Int, Somjit; Sonsilphong, Suphachoke; Wanchai, Paweena

2017-01-01

Within the numerous and heterogeneous web services offered through different sources, automatic web services composition is the most convenient method for building complex business processes that permit invocation of multiple existing atomic services. The current solutions in functional web services composition lack autonomous queries of semantic matches within the parameters of web services, which are necessary in the composition of large-scale related services. In this paper, we propose a graph-based Semantic Web Services composition system consisting of two subsystems: management time and run time. The management-time subsystem is responsible for dependency graph preparation in which a dependency graph of related services is generated automatically according to the proposed semantic matchmaking rules. The run-time subsystem is responsible for discovering the potential web services and nonredundant web services composition of a user's query using a graph-based searching algorithm. The proposed approach was applied to healthcare data integration in different health organizations and was evaluated according to two aspects: execution time measurement and correctness measurement.

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

Science.gov (United States)

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.

Scaling the walls of discovery: using semantic metadata for integrative problem solving.

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Manning, Maurice; Aggarwal, Amit; Gao, Kevin; Tucker-Kellogg, Greg

2009-03-01

Current data integration approaches by bioinformaticians frequently involve extracting data from a wide variety of public and private data repositories, each with a unique vocabulary and schema, via scripts. These separate data sets must then be normalized through the tedious and lengthy process of resolving naming differences and collecting information into a single view. Attempts to consolidate such diverse data using data warehouses or federated queries add significant complexity and have shown limitations in flexibility. The alternative of complete semantic integration of data requires a massive, sustained effort in mapping data types and maintaining ontologies. We focused instead on creating a data architecture that leverages semantic mapping of experimental metadata, to support the rapid prototyping of scientific discovery applications with the twin goals of reducing architectural complexity while still leveraging semantic technologies to provide flexibility, efficiency and more fully characterized data relationships. A metadata ontology was developed to describe our discovery process. A metadata repository was then created by mapping metadata from existing data sources into this ontology, generating RDF triples to describe the entities. Finally an interface to the repository was designed which provided not only search and browse capabilities but complex query templates that aggregate data from both RDF and RDBMS sources. We describe how this approach (i) allows scientists to discover and link relevant data across diverse data sources and (ii) provides a platform for development of integrative informatics applications.

Integrating semantic dimension into openEHR archetypes for the management of cerebral palsy electronic medical records.

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Ellouze, Afef Samet; Bouaziz, Rafik; Ghorbel, Hanen

2016-10-01

using a knowledge base which we have constructed by interviews with domain experts, (ii) translation of initially CP ADL archetypes into CP OWL-DL archetypes, (iii) creation of an ontological source which we can use to annotate obtained archetypes and (vi) enrichment and supply of the ontological source and integration of semantic relations by providing hence fueling the ontology with new concepts, ensuring consistency and eliminating ambiguity between concepts. The degree of semantic interoperability that could be reached between EMR systems depends strongly on the quality of the used archetypes. Thus, the integration of semantic dimension in archetypes modeling process is crucial. By creating an ontological source and annotating archetypes, we create a supportive platform ensuring semantic interoperability between archetypes-based EMR-systems. Copyright © 2016. Published by Elsevier Inc.

Improving integrative searching of systems chemical biology data using semantic annotation.

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Chen, Bin; Ding, Ying; Wild, David J

2012-03-08

Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and biology. We previously developed an RDF-based resource called Chem2Bio2RDF that enabled querying of such data using the SPARQL query language. Whilst this work has proved useful in its own right as one of the first major resources in these disciplines, its utility could be greatly improved by the application of an ontology for annotation of the nodes and edges in the RDF graph, enabling a much richer range of semantic queries to be issued. We developed a generalized chemogenomics and systems chemical biology OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. The ontology also includes data provenance. We used it to annotate our Chem2Bio2RDF dataset, making it a rich semantic resource. Through a series of scientific case studies we demonstrate how this (i) simplifies the process of building SPARQL queries, (ii) enables useful new kinds of queries on the data and (iii) makes possible intelligent reasoning and semantic graph mining in chemogenomics and systems chemical biology. Chem2Bio2OWL is available at http://chem2bio2rdf.org/owl. The document is available at http://chem2bio2owl.wikispaces.com.

Semantic integration of gene expression analysis tools and data sources using software connectors

Science.gov (United States)

2013-01-01

Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools

Semantic Business Intelligence - a New Generation of Business Intelligence

Directory of Open Access Journals (Sweden)

Dinu AIRINEI

2012-01-01

Full Text Available Business Intelligence Solutions represents applications used by companies to manage process and analyze data to provide substantiated decision. In the context of Semantic Web develop-ment trend is to integrate semantic unstructured data, making business intelligence solutions to be redesigned in such a manner that can analyze, process and synthesize, in addition to traditional data and data integrated with semantic another form and structure. This invariably leads appearance of new BI solution, called Semantic Business Intelligence.

Improving integrative searching of systems chemical biology data using semantic annotation

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Chen Bin

2012-03-01

Full Text Available Abstract Background Systems chemical biology and chemogenomics are considered critical, integrative disciplines in modern biomedical research, but require data mining of large, integrated, heterogeneous datasets from chemistry and biology. We previously developed an RDF-based resource called Chem2Bio2RDF that enabled querying of such data using the SPARQL query language. Whilst this work has proved useful in its own right as one of the first major resources in these disciplines, its utility could be greatly improved by the application of an ontology for annotation of the nodes and edges in the RDF graph, enabling a much richer range of semantic queries to be issued. Results We developed a generalized chemogenomics and systems chemical biology OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. The ontology also includes data provenance. We used it to annotate our Chem2Bio2RDF dataset, making it a rich semantic resource. Through a series of scientific case studies we demonstrate how this (i simplifies the process of building SPARQL queries, (ii enables useful new kinds of queries on the data and (iii makes possible intelligent reasoning and semantic graph mining in chemogenomics and systems chemical biology. Availability Chem2Bio2OWL is available at http://chem2bio2rdf.org/owl. The document is available at http://chem2bio2owl.wikispaces.com.

Designing equivalent semantic models for process creation

NARCIS (Netherlands)

P.H.M. America (Pierre); J.W. de Bakker (Jaco)

1986-01-01

textabstractOperational and denotational semantic models are designed for languages with process creation, and the relationships between the two semantics are investigated. The presentation is organized in four sections dealing with a uniform and static, a uniform and dynamic, a nonuniform and

Distributed Database Semantic Integration of Wireless Sensor Network to Access the Environmental Monitoring System

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Ubaidillah Umar

2018-06-01

Full Text Available A wireless sensor network (WSN works continuously to gather information from sensors that generate large volumes of data to be handled and processed by applications. Current efforts in sensor networks focus more on networking and development services for a variety of applications and less on processing and integrating data from heterogeneous sensors. There is an increased need for information to become shareable across different sensors, database platforms, and applications that are not easily implemented in traditional database systems. To solve the issue of these large amounts of data from different servers and database platforms (including sensor data, a semantic sensor web service platform is needed to enable a machine to extract meaningful information from the sensor’s raw data. This additionally helps to minimize and simplify data processing and to deduce new information from existing data. This paper implements a semantic web data platform (SWDP to manage the distribution of data sensors based on the semantic database system. SWDP uses sensors for temperature, humidity, carbon monoxide, carbon dioxide, luminosity, and noise. The system uses the Sesame semantic web database for data processing and a WSN to distribute, minimize, and simplify information processing. The sensor nodes are distributed in different places to collect sensor data. The SWDP generates context information in the form of a resource description framework. The experiment results demonstrate that the SWDP is more efficient than the traditional database system in terms of memory usage and processing time.

Topic structure affects semantic integration: evidence from event-related potentials.

Science.gov (United States)

Yang, Xiaohong; Chen, Xuhai; Chen, Shuang; Xu, Xiaoying; Yang, Yufang

2013-01-01

This study investigated whether semantic integration in discourse context could be influenced by topic structure using event-related brain potentials. Participants read discourses in which the last sentence contained a critical word that was either congruent or incongruent with the topic established in the first sentence. The intervening sentences between the first and the last sentence of the discourse either maintained or shifted the original topic. Results showed that incongruent words in topic-maintained discourses elicited an N400 effect that was broadly distributed over the scalp while those in topic-shifted discourses elicited an N400 effect that was lateralized to the right hemisphere and localized over central and posterior areas. Moreover, a late positivity effect was only elicited by incongruent words in topic-shifted discourses, but not in topic-maintained discourses. This suggests an important role for discourse structure in semantic integration, such that compared with topic-maintained discourses, the complexity of discourse structure in topic-shifted condition reduces the initial stage of semantic integration and enhances the later stage in which a mental representation is updated.

Integrated Semantics Service Platform for the Internet of Things: A Case Study of a Smart Office

Science.gov (United States)

Ryu, Minwoo; Kim, Jaeho; Yun, Jaeseok

2015-01-01

The Internet of Things (IoT) allows machines and devices in the world to connect with each other and generate a huge amount of data, which has a great potential to provide useful knowledge across service domains. Combining the context of IoT with semantic technologies, we can build integrated semantic systems to support semantic interoperability. In this paper, we propose an integrated semantic service platform (ISSP) to support ontological models in various IoT-based service domains of a smart city. In particular, we address three main problems for providing integrated semantic services together with IoT systems: semantic discovery, dynamic semantic representation, and semantic data repository for IoT resources. To show the feasibility of the ISSP, we develop a prototype service for a smart office using the ISSP, which can provide a preset, personalized office environment by interpreting user text input via a smartphone. We also discuss a scenario to show how the ISSP-based method would help build a smart city, where services in each service domain can discover and exploit IoT resources that are wanted across domains. We expect that our method could eventually contribute to providing people in a smart city with more integrated, comprehensive services based on semantic interoperability. PMID:25608216

Integrated Semantics Service Platform for the Internet of Things: A Case Study of a Smart Office

Directory of Open Access Journals (Sweden)

Minwoo Ryu

2015-01-01

Full Text Available The Internet of Things (IoT allows machines and devices in the world to connect with each other and generate a huge amount of data, which has a great potential to provide useful knowledge across service domains. Combining the context of IoT with semantic technologies, we can build integrated semantic systems to support semantic interoperability. In this paper, we propose an integrated semantic service platform (ISSP to support ontological models in various IoT-based service domains of a smart city. In particular, we address three main problems for providing integrated semantic services together with IoT systems: semantic discovery, dynamic semantic representation, and semantic data repository for IoT resources. To show the feasibility of the ISSP, we develop a prototype service for a smart office using the ISSP, which can provide a preset, personalized office environment by interpreting user text input via a smartphone. We also discuss a scenario to show how the ISSP-based method would help build a smart city, where services in each service domain can discover and exploit IoT resources that are wanted across domains. We expect that our method could eventually contribute to providing people in a smart city with more integrated, comprehensive services based on semantic interoperability.

Integrated semantics service platform for the Internet of Things: a case study of a smart office.

Science.gov (United States)

Ryu, Minwoo; Kim, Jaeho; Yun, Jaeseok

2015-01-19

The Internet of Things (IoT) allows machines and devices in the world to connect with each other and generate a huge amount of data, which has a great potential to provide useful knowledge across service domains. Combining the context of IoT with semantic technologies, we can build integrated semantic systems to support semantic interoperability. In this paper, we propose an integrated semantic service platform (ISSP) to support ontological models in various IoT-based service domains of a smart city. In particular, we address three main problems for providing integrated semantic services together with IoT systems: semantic discovery, dynamic semantic representation, and semantic data repository for IoT resources. To show the feasibility of the ISSP, we develop a prototype service for a smart office using the ISSP, which can provide a preset, personalized office environment by interpreting user text input via a smartphone. We also discuss a scenario to show how the ISSP-based method would help build a smart city, where services in each service domain can discover and exploit IoT resources that are wanted across domains. We expect that our method could eventually contribute to providing people in a smart city with more integrated, comprehensive services based on semantic interoperability.

ERPs, semantic processing and age.

Science.gov (United States)

Miyamoto, T; Katayama, J; Koyama, T

1998-06-01

ERPs (N400, LPC and CNV) were elicited in two sets of subjects grouped according to age (young vs. elderly) using a word-pair category matching paradigm. Each prime consisted of a Japanese noun (constructed from two to four characters of the Hiragana) followed by one Chinese character (Kanji) as the target, this latter representing one of five semantic categories. There were two equally probable target conditions: match or mismatch. Each target was preceded by a prime, either belonging to, or not belonging to, the same semantic category. The subjects were required to respond with a specified button press to the given target according to the condition. We found RTs to be longer in the elderly subjects and under the mismatch condition. N400 amplitude was reduced in the elderly subjects under the mismatch condition and there was no difference between match and mismatch response, which were similar in amplitude to that under match condition for the young subjects. In addition, the CNV amplitudes were larger in the elderly subjects. These results suggested that functional changes in semantic processing through aging (larger semantic networks and diffuse semantic activation) were the cause of this N400 reduction, attributing a subsidiary role to attentional disturbance. We also discuss the importance of taking age-related changes into consideration in clinical studies.

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

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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.

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

Science.gov (United States)

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.

Semantic Business Intelligence - a New Generation of Business Intelligence

OpenAIRE

Dinu AIRINEI; Dora-Anca BERTA

2012-01-01

Business Intelligence Solutions represents applications used by companies to manage process and analyze data to provide substantiated decision. In the context of Semantic Web develop-ment trend is to integrate semantic unstructured data, making business intelligence solutions to be redesigned in such a manner that can analyze, process and synthesize, in addition to traditional data and data integrated with semantic another form and structure. This invariably leads appearance of new BI solutio...

Flexible recruitment of semantic richness: Context modulates body-object interaction effects in lexical-semantic processing

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Cody eTousignant

2012-03-01

Full Text Available Body-object interaction (BOI is a semantic richness variable that measures the perceived ease with which the human body can physically interact with a word’s referent. Lexical and semantic processing is facilitated when words are associated with relatively more bodily experience (high BOI words, e.g., belt. To date, BOI effects have been examined in only one semantic decision context (is it imageable?. It has been argued that semantic processing is dynamic and can be modulated by context. We examined these influences by testing how task knowledge modulated BOI effects. We presented the same stimuli (high- and low-BOI entity words and a set of action words in each of four action/entity semantic categorization tasks (SCTs. Task framing was manipulated: participants were told about one (actions or entities or both (actions and entities categories of words in the decision task. Facilitatory BOI effects were observed when participants knew that ‘entity’ was part of the decision category, regardless of whether the high- and low-BOI entity words appeared on the affirmative or negative side of the decision. That BOI information was only useful when participants had expectations that object words would be presented suggests a strong role for the decision context in lexical-semantic processing, and supports a dynamic view of conceptual knowledge.

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

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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.

Semantic processes leading to true and false memory formation in schizophrenia.

Science.gov (United States)

Paz-Alonso, Pedro M; Ghetti, Simona; Ramsay, Ian; Solomon, Marjorie; Yoon, Jong; Carter, Cameron S; Ragland, J Daniel

2013-07-01

Encoding semantic relationships between items on word lists (semantic processing) enhances true memories, but also increases memory distortions. Episodic memory impairments in schizophrenia (SZ) are strongly driven by failures to process semantic relations, but the exact nature of these relational semantic processing deficits is not well understood. Here, we used a false memory paradigm to investigate the impact of implicit and explicit semantic processing manipulations on episodic memory in SZ. Thirty SZ and 30 demographically matched healthy controls (HC) studied Deese/Roediger-McDermott (DRM) lists of semantically associated words. Half of the lists had strong implicit semantic associations and the remainder had low strength associations. Similarly, half of the lists were presented under "standard" instructions and the other half under explicit "relational processing" instructions. After study, participants performed recall and old/new recognition tests composed of targets, critical lures, and unrelated lures. HC exhibited higher true memories and better discriminability between true and false memory compared to SZ. High, versus low, associative strength increased false memory rates in both groups. However, explicit "relational processing" instructions positively improved true memory rates only in HC. Finally, true and false memory rates were associated with severity of disorganized and negative symptoms in SZ. These results suggest that reduced processing of semantic relationships during encoding in SZ may stem from an inability to implement explicit relational processing strategies rather than a fundamental deficit in the implicit activation and retrieval of word meanings from patients' semantic lexicon. Copyright © 2013 Elsevier B.V. All rights reserved.

Orthographic and Semantic Processing in Young Readers

Science.gov (United States)

Polse, Lara R.; Reilly, Judy S.

2015-01-01

This investigation examined orthographic and semantic processing during reading acquisition. Children in first to fourth grade were presented with a target word and two response alternatives, and were asked to identify the semantic match. Words were presented in four conditions: an exact match and unrelated foil (STONE-STONE-EARS), an exact match…

Evidence for the contribution of a threshold retrieval process to semantic memory.

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Kempnich, Maria; Urquhart, Josephine A; O'Connor, Akira R; Moulin, Chris J A

2017-10-01

It is widely held that episodic retrieval can recruit two processes: a threshold context retrieval process (recollection) and a continuous signal strength process (familiarity). Conversely the processes recruited during semantic retrieval are less well specified. We developed a semantic task analogous to single-item episodic recognition to interrogate semantic recognition receiver-operating characteristics (ROCs) for a marker of a threshold retrieval process. We fitted observed ROC points to three signal detection models: two models typically used in episodic recognition (unequal variance and dual-process signal detection models) and a novel dual-process recollect-to-reject (DP-RR) signal detection model that allows a threshold recollection process to aid both target identification and lure rejection. Given the nature of most semantic questions, we anticipated the DP-RR model would best fit the semantic task data. Experiment 1 (506 participants) provided evidence for a threshold retrieval process in semantic memory, with overall best fits to the DP-RR model. Experiment 2 (316 participants) found within-subjects estimates of episodic and semantic threshold retrieval to be uncorrelated. Our findings add weight to the proposal that semantic and episodic memory are served by similar dual-process retrieval systems, though the relationship between the two threshold processes needs to be more fully elucidated.

Predicting Protein Function via Semantic Integration of Multiple Networks.

Science.gov (United States)

Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

Role of consciousness in temporal integration of semantic information.

Science.gov (United States)

Yang, Yung-Hao; Tien, Yung-Hsuan; Yang, Pei-Ling; Yeh, Su-Ling

2017-10-01

Previous studies found that word meaning can be processed unconsciously. Yet it remains unknown whether temporally segregated words can be integrated into a holistic meaningful phrase without consciousness. The first four experiments were designed to examine this by sequentially presenting the first three words of Chinese four-word idioms as prime to one eye and dynamic Mondrians to the other (i.e., the continuous flash suppression paradigm; CFS). An unmasked target word followed the three masked words in a lexical decision task. Results from such invisible (CFS) condition were compared with the visible condition where the preceding words were superimposed on the Mondrians and presented to both eyes. Lower performance in behavioral experiments and larger N400 event-related potentials (ERP) component for incongruent- than congruent-ending words were found in the visible condition. However, no such congruency effect was found in the invisible condition, even with enhanced statistical power and top-down attention, and with several potential confounding factors (contrast-dependent processing, long interval, no conscious training) excluded. Experiment 5 demonstrated that familiarity of word orientation without temporal integration can be processed unconsciously, excluding the possibility of general insensitivity of our paradigm. The overall result pattern therefore suggests that consciousness plays an important role in semantic temporal integration in the conditions we tested.

Age-related reduction of adaptive brain response during semantic integration is associated with gray matter reduction.

Directory of Open Access Journals (Sweden)

Zude Zhu

Full Text Available While aging is associated with increased knowledge, it is also associated with decreased semantic integration. To investigate brain activation changes during semantic integration, a sample of forty-eight 25-75 year-old adults read sentences with high cloze (HC and low cloze (LC probability while functional magnetic resonance imaging was conducted. Significant age-related reduction of cloze effect (LC vs. HC was found in several regions, especially the left middle frontal gyrus (MFG and right inferior frontal gyrus (IFG, which play an important role in semantic integration. Moreover, when accounting for global gray matter volume reduction, the age-cloze correlation in the left MFG and right IFG was absent. The results suggest that brain structural atrophy may disrupt brain response in aging brains, which then show less brain engagement in semantic integration.

Language and culture modulate online semantic processing.

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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.

Ontology-based approaches for cross-enterprise collaboration: a literature review on semantic business process management

Science.gov (United States)

Hoang, Hanh H.; Jung, Jason J.; Tran, Chi P.

2014-11-01

Based on an in-depth analysis of the existing approaches in applying semantic technologies to business process management (BPM) research in the perspective of cross-enterprise collaboration or so-called business-to-business integration, we analyse, discuss and compare methodologies, applications and best practices of the surveyed approaches with the proposed criteria. This article identifies various relevant research directions in semantic BPM (SBPM). Founded on the result of our investigation, we summarise the state of art of SBPM. We also address areas and directions for further research activities.

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

Science.gov (United States)

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.

Context effects in embodied lexical-semantic processing

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Wessel O Van Dam

2010-10-01

Full Text Available The embodied view of language comprehension proposes that the meaning of words is grounded in perception and action rather than represented in abstract amodal symbols. Support for embodied theories of language processing comes from behavioural studies showing that understanding a sentence about an action can modulate congruent and incongruent physical responses, suggesting motor involvement during comprehension of sentences referring to bodily movement. Additionally, several neuroimaging studies have provided evidence that comprehending single words denoting manipulable objects elicits specific responses in the neural motor system. An interesting question that remains is whether action semantic knowledge is directly activated as motor simulations in the brain, or rather modulated by the semantic context in which action words are encountered. In the current paper we investigated the nature of conceptual representations using a go/no-go lexical decision task. Specifically, target words were either presented in a semantic context that emphasized dominant action features (features related to the functional use of an object or non-dominant action features. The response latencies in a lexical decision task reveal that participants were faster to respond to words denoting objects for which the functional use was congruent with the prepared movement. This facilitation effect, however, was only apparent when the semantic context emphasized corresponding motor properties. These findings suggest that motor involvement during comprehension of sentences is not automatic. Rather, the results suggest that conceptual processing is a context-dependent process that incorporates motor-related knowledge in a flexible manner.

Exploring and linking biomedical resources through multidimensional semantic spaces.

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Berlanga, Rafael; Jiménez-Ruiz, Ernesto; Nebot, Victoria

2012-01-25

The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for

A semantic data dictionary method for database schema integration in CIESIN

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Hinds, N.; Huang, Y.; Ravishankar, C.

1993-08-01

CIESIN (Consortium for International Earth Science Information Network) is funded by NASA to investigate the technology necessary to integrate and facilitate the interdisciplinary use of Global Change information. A clear of this mission includes providing a link between the various global change data sets, in particular the physical sciences and the human (social) sciences. The typical scientist using the CIESIN system will want to know how phenomena in an outside field affects his/her work. For example, a medical researcher might ask: how does air-quality effect emphysema? This and many similar questions will require sophisticated semantic data integration. The researcher who raised the question may be familiar with medical data sets containing emphysema occurrences. But this same investigator may know little, if anything, about the existance or location of air-quality data. It is easy to envision a system which would allow that investigator to locate and perform a ``join'' on two data sets, one containing emphysema cases and the other containing air-quality levels. No such system exists today. One major obstacle to providing such a system will be overcoming the heterogeneity which falls into two broad categories. ``Database system'' heterogeneity involves differences in data models and packages. ``Data semantic'' heterogeneity involves differences in terminology between disciplines which translates into data semantic issues, and varying levels of data refinement, from raw to summary. Our work investigates a global data dictionary mechanism to facilitate a merged data service. Specially, we propose using a semantic tree during schema definition to aid in locating and integrating heterogeneous databases.

Integration of Neuroimaging and Microarray Datasets  through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

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Spiro P. Pantazatos

2009-06-01

Full Text Available An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP and a knowledge-based phenotype organizer system (PhenOS to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®. The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50, and precision of the semantic mapping between these terms across datasets was 98% (n = 100. To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets.

Semantic processing in deaf and hard-of-hearing children: Large N400 mismatch effects in brain responses, despite poor semantic ability

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Petter Kallioinen

2016-08-01

Full Text Available Difficulties in auditory and phonological processing affect semantic processing in speech comprehension of deaf and hard-of-hearing (DHH children. However, little is known about brain responses of semantic processing in this group. We investigated event-related potentials (ERPs in DHH children with cochlear implants (CI and/or hearing aids (HA, and in normally hearing controls (NH. We used a semantic priming task with spoken word primes followed by picture targets. In both DHH children and controls, response differences between matching and mismatching targets revealed a typical N400-effect associated with semantic processing. Children with CI had the largest mismatch response despite poor semantic abilities overall, children with CI also had the largest ERP differentiation between mismatch types, with small effects of within-category mismatches (target from same category as prime and large effects between-category mismatches (were target is from a different category than prime. NH and HA children had similar responses to both mismatch types. While the large and differentiated ERP responses in the CI group were unexpected and should be interpreted with caution, the results could reflect less precision in semantic processing among children with CI, or a stronger reliance on predictive processing.

CI-Miner: A Semantic Methodology to Integrate Scientists, Data and Documents through the Use of Cyber-Infrastructure

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Pinheiro da Silva, P.; CyberShARE Center of Excellence

2011-12-01

Scientists today face the challenge of rethinking the manner in which they document and make available their processes and data in an international cyber-infrastructure of shared resources. Some relevant examples of new scientific practices in the realm of computational and data extraction sciences include: large scale data discovery; data integration; data sharing across distinct scientific domains, systematic management of trust and uncertainty; and comprehensive support for explaining processes and results. This talk introduces CI-Miner - an innovative hands-on, open-source, community-driven methodology to integrate these new scientific practices. It has been developed in collaboration with scientists, with the purpose of capturing, storing and retrieving knowledge about scientific processes and their products, thereby further supporting a new generation of science techniques based on data exploration. CI-Miner uses semantic annotations in the form of W3C Ontology Web Language-based ontologies and Proof Markup Language (PML)-based provenance to represent knowledge. This methodology specializes in general-purpose ontologies, projected into workflow-driven ontologies(WDOs) and into semantic abstract workflows (SAWs). Provenance in PML is CI-Miner's integrative component, which allows scientists to retrieve and reason with the knowledge represented in these new semantic documents. It serves additionally as a platform to share such collected knowledge with the scientific community participating in the international cyber-infrastructure. The integrated semantic documents that are tailored for the use of human epistemic agents may also be utilized by machine epistemic agents, since the documents are based on W3C Resource Description Framework (RDF) notation. This talk is grounded upon interdisciplinary lessons learned through the use of CI-Miner in support of government-funded national and international cyber-infrastructure initiatives in the areas of geo

Sharing human-generated observations by integrating HMI and the Semantic Sensor Web.

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Sigüenza, Alvaro; Díaz-Pardo, David; Bernat, Jesús; Vancea, Vasile; Blanco, José Luis; Conejero, David; Gómez, Luis Hernández

2012-01-01

Current "Internet of Things" concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C's Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers' observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is sound.

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

Science.gov (United States)

Waagmeester, Andra; Kutmon, Martina; Riutta, Anders; Miller, Ryan; Willighagen, Egon L; Evelo, Chris T; Pico, Alexander R

2016-06-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

Directory of Open Access Journals (Sweden)

Andra Waagmeester

2016-06-01

Full Text Available The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources

Science.gov (United States)

Waagmeester, Andra; Pico, Alexander R.

2016-01-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web. PMID:27336457

Effect of semantic coherence on episodic memory processes in schizophrenia.

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Battal Merlet, Lâle; Morel, Shasha; Blanchet, Alain; Lockman, Hazlin; Kostova, Milena

2014-12-30

Schizophrenia is associated with severe episodic retrieval impairment. The aim of this study was to investigate the possibility that schizophrenia patients could improve their familiarity and/or recollection processes by manipulating the semantic coherence of to-be-learned stimuli and using deep encoding. Twelve schizophrenia patients and 12 healthy controls of comparable age, gender, and educational level undertook an associative recognition memory task. The stimuli consisted of pairs of words that were either related or unrelated to a given semantic category. The process dissociation procedure was used to calculate the estimates of familiarity and recollection processes. Both groups showed enhanced memory performances for semantically related words. However, in healthy controls, semantic relatedness led to enhanced recollection, while in schizophrenia patients, it induced enhanced familiarity. The familiarity estimates for related words were comparable in both groups, indicating that familiarity could be used as a compensatory mechanism in schizophrenia patients. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Semantic Web integration of Cheminformatics resources with the SADI framework

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Chepelev Leonid L

2011-05-01

Full Text Available Abstract Background The diversity and the largely independent nature of chemical research efforts over the past half century are, most likely, the major contributors to the current poor state of chemical computational resource and database interoperability. While open software for chemical format interconversion and database entry cross-linking have partially addressed database interoperability, computational resource integration is hindered by the great diversity of software interfaces, languages, access methods, and platforms, among others. This has, in turn, translated into limited reproducibility of computational experiments and the need for application-specific computational workflow construction and semi-automated enactment by human experts, especially where emerging interdisciplinary fields, such as systems chemistry, are pursued. Fortunately, the advent of the Semantic Web, and the very recent introduction of RESTful Semantic Web Services (SWS may present an opportunity to integrate all of the existing computational and database resources in chemistry into a machine-understandable, unified system that draws on the entirety of the Semantic Web. Results We have created a prototype framework of Semantic Automated Discovery and Integration (SADI framework SWS that exposes the QSAR descriptor functionality of the Chemistry Development Kit. Since each of these services has formal ontology-defined input and output classes, and each service consumes and produces RDF graphs, clients can automatically reason about the services and available reference information necessary to complete a given overall computational task specified through a simple SPARQL query. We demonstrate this capability by carrying out QSAR analysis backed by a simple formal ontology to determine whether a given molecule is drug-like. Further, we discuss parameter-based control over the execution of SADI SWS. Finally, we demonstrate the value of computational resource

A case study of data integration for aquatic resources using semantic web technologies

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Gordon, Janice M.; Chkhenkeli, Nina; Govoni, David L.; Lightsom, Frances L.; Ostroff, Andrea C.; Schweitzer, Peter N.; Thongsavanh, Phethala; Varanka, Dalia E.; Zednik, Stephan

2015-01-01

Use cases, information modeling, and linked data techniques are Semantic Web technologies used to develop a prototype system that integrates scientific observations from four independent USGS and cooperator data systems. The techniques were tested with a use case goal of creating a data set for use in exploring potential relationships among freshwater fish populations and environmental factors. The resulting prototype extracts data from the BioData Retrieval System, the Multistate Aquatic Resource Information System, the National Geochemical Survey, and the National Hydrography Dataset. A prototype user interface allows a scientist to select observations from these data systems and combine them into a single data set in RDF format that includes explicitly defined relationships and data definitions. The project was funded by the USGS Community for Data Integration and undertaken by the Community for Data Integration Semantic Web Working Group in order to demonstrate use of Semantic Web technologies by scientists. This allows scientists to simultaneously explore data that are available in multiple, disparate systems beyond those they traditionally have used.

An Investigation into Semantic and Phonological Processing in Individuals with Williams Syndrome

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Lee, Cheryl S.; Binder, Katherine S.

2014-01-01

Purpose: The current study examined semantic and phonological processing in individuals with Williams syndrome (WS). Previous research in language processing in individuals with WS suggests a complex linguistic system characterized by "deviant" semantic organization and differential phonological processing. Method: Two experiments…

Semantic Web meets Integrative Biology: a survey.

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Chen, Huajun; Yu, Tong; Chen, Jake Y

2013-01-01

Integrative Biology (IB) uses experimental or computational quantitative technologies to characterize biological systems at the molecular, cellular, tissue and population levels. IB typically involves the integration of the data, knowledge and capabilities across disciplinary boundaries in order to solve complex problems. We identify a series of bioinformatics problems posed by interdisciplinary integration: (i) data integration that interconnects structured data across related biomedical domains; (ii) ontology integration that brings jargons, terminologies and taxonomies from various disciplines into a unified network of ontologies; (iii) knowledge integration that integrates disparate knowledge elements from multiple sources; (iv) service integration that build applications out of services provided by different vendors. We argue that IB can benefit significantly from the integration solutions enabled by Semantic Web (SW) technologies. The SW enables scientists to share content beyond the boundaries of applications and websites, resulting into a web of data that is meaningful and understandable to any computers. In this review, we provide insight into how SW technologies can be used to build open, standardized and interoperable solutions for interdisciplinary integration on a global basis. We present a rich set of case studies in system biology, integrative neuroscience, bio-pharmaceutics and translational medicine, to highlight the technical features and benefits of SW applications in IB.

Integrating deep and shallow natural language processing components : representations and hybrid architectures

OpenAIRE

Schäfer, Ulrich

2006-01-01

We describe basic concepts and software architectures for the integration of shallow and deep (linguistics-based, semantics-oriented) natural language processing (NLP) components. The main goal of this novel, hybrid integration paradigm is improving robustness of deep processing. After an introduction to constraint-based natural language parsing, we give an overview of typical shallow processing tasks. We introduce XML standoff markup as an additional abstraction layer that eases integration ...

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

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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 effects of gender and self-insight on early semantic processing.

Directory of Open Access Journals (Sweden)

Xu Xu

Full Text Available This event-related potential (ERP study explored individual differences associated with gender and level of self-insight in early semantic processing. Forty-eight Chinese native speakers completed a semantic judgment task with three different categories of words: abstract neutral words (e.g., logic, effect, concrete neutral words (e.g., teapot, table, and emotion words (e.g., despair, guilt. They then assessed their levels of self-insight. Results showed that women engaged in greater processing than did men. Gender differences also manifested in the relationship between level of self-insight and word processing. For women, level of self-insight was associated with level of semantic activation for emotion words and abstract neutral words, but not for concrete neutral words. For men, level of self-insight was related to processing speed, particularly in response to abstract and concrete neutral words. These findings provide electrophysiological evidence for the effects of gender and self-insight on semantic processing and highlight the need to take into consideration subject variables in related research.

Evaluation of semantic aspect of language in students of ordinary, integrated and special schools

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Ali Ghorbani

2012-06-01

Full Text Available Background and Aim: Children with severe and profound hearing loss have difficulties in communicating with others and educating at school. Effects of learning environment on children's language skills have been recently focused and educating those students in ordinary schools has been proposed. According to this view, we compared perception of antonyms and synonyms as a semantic aspect of language in students of ordinary, integrated and special schools.Methods: It was an analytic cross-sectional study. Three groups of students were enrolled: normal-hearing students of ordinary schools and hearing-loss students of integrated and specials schools. Each group consisted of 25 students in fifth grade of elementary schools in Tehran city. Two written tests were used. Subjects wrote synonyms and antonyms for each word in the tests.Results: Results denoted significant differences between scores of normal-hearing and hearing-loss students and also between hearing-loss students of integrated schools and hearing-loss students of special schools (p<0.05. In all three groups of the students, perception of antonyms was better than antonyms (p<0.001. Speech processing rate in normal-hearing students were higher than both groups of hearing-loss students (p<0.001.Conclusion: The differences between normal-hearing and hearing-loss students shows that similar to other language skills, perception of synonyms and antonyms as a semantic aspect of speech is related to the hearing conditions and type of education. Moreover, the differences between two groups of hearing-loss students represent that speech stimulants and interaction with normal-hearing children could improve semantic aspect of speech in hearing-loss students.

Neural Substrates of Semantic Prospection – Evidence from the Dementias

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Irish, Muireann; Eyre, Nadine; Dermody, Nadene; O’Callaghan, Claire; Hodges, John R.; Hornberger, Michael; Piguet, Olivier

2016-01-01

The ability to envisage personally relevant events at a future time point represents an incredibly sophisticated cognitive endeavor and one that appears to be intimately linked to episodic memory integrity. Far less is known regarding the neurocognitive mechanisms underpinning the capacity to envisage non-personal future occurrences, known as semantic future thinking. Moreover the degree of overlap between the neural substrates supporting episodic and semantic forms of prospection remains unclear. To this end, we sought to investigate the capacity for episodic and semantic future thinking in Alzheimer’s disease (n = 15) and disease-matched behavioral-variant frontotemporal dementia (n = 15), neurodegenerative disorders characterized by significant medial temporal lobe (MTL) and frontal pathology. Participants completed an assessment of past and future thinking across personal (episodic) and non-personal (semantic) domains, as part of a larger neuropsychological battery investigating episodic and semantic processing, and their performance was contrasted with 20 age- and education-matched healthy older Controls. Participants underwent whole-brain T1-weighted structural imaging and voxel-based morphometry analysis was conducted to determine the relationship between gray matter integrity and episodic and semantic future thinking. Relative to Controls, both patient groups displayed marked future thinking impairments, extending across episodic and semantic domains. Analyses of covariance revealed that while episodic future thinking deficits could be explained solely in terms of episodic memory proficiency, semantic prospection deficits reflected the interplay between episodic and semantic processing. Distinct neural correlates emerged for each form of future simulation with differential involvement of prefrontal, lateral temporal, and medial temporal regions. Notably, the hippocampus was implicated irrespective of future thinking domain, with the suggestion of

Neural Substrates of Semantic Prospection – Evidence from the Dementias

Directory of Open Access Journals (Sweden)

Muireann eIrish

2016-05-01

Full Text Available The ability to envisage personally relevant events at a future time point represents an incredibly sophisticated cognitive endeavor and one that appears to be intimately linked to episodic memory integrity. Far less is known regarding the neurocognitive mechanisms underpinning the capacity to envisage non-personal future occurrences, known as semantic future thinking. Moreover the degree of overlap between the neural substrates supporting episodic and semantic forms of prospection remains unclear. To this end, we sought to investigate the capacity for episodic and semantic future thinking in Alzheimer’s disease (n = 15 and disease-matched behavioral-variant frontotemporal dementia (n = 15, neurodegenerative disorders characterized by significant medial temporal lobe and frontal pathology. Participants completed an assessment of past and future thinking across personal (episodic and non-personal (semantic domains, as part of a larger neuropsychological battery investigating episodic and semantic processing, and their performance was contrasted with 20 age- and education-matched healthy older Controls. Participants underwent whole-brain T1 weighted structural imaging and voxel-based morphometry analysis was conducted to determine the relationship between grey matter integrity and episodic and semantic future thinking. Relative to Controls, both patient groups displayed marked future thinking impairments, extending across episodic and semantic domains. Analyses of covariance revealed that while episodic future thinking deficits could be explained solely in terms of episodic memory proficiency, semantic prospection deficits reflected the interplay between episodic and semantic processing. Distinct neural correlates emerged for each form of future simulation with differential involvement of prefrontal, lateral temporal and medial temporal regions. Notably, the hippocampus was implicated irrespective of future thinking domain, with the suggestion of

An fMRI study of semantic processing in men with schizophrenia

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Kubicki, M.; McCarley, R.W.; Nestor, P.G.; Huh, T.; Kikinis, R.; Shenton, M.E.; Wible, C.G.

2009-01-01

As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditions. Under the deep, semantic encoding condition, subjects made semantic judgments as to whether the words were abstract or concrete. Under the shallow, nonsemantic encoding condition, subjects made perceptual judgments of the font size (uppercase/lowercase) of the presented words. After performance of the behavioral task, a recognition test was used to assess the depth of processing effect, defined as better performance for semantically encoded words than for perceptually encoded words. For the scanned version only, the words for both conditions were repeated in order to assess repetition-priming effects. Reaction times were assessed in both testing scenarios. Both groups showed the expected depth of processing effect for recognition, and control subjects showed the expected increased activation of the left inferior prefrontal cortex (LIPC) under semantic encoding relative to perceptual encoding conditions as well as repetition priming for semantic conditions only. In contrast, schizophrenics showed similar patterns of fMRI activation regardless of condition. Most striking in relation to controls, patients showed decreased LIFC activation concurrent with increased left superior temporal gyrus activation for semantic encoding versus shallow encoding. Furthermore, schizophrenia subjects did not show the repetition priming effect, either behaviorally or as a decrease in LIPC activity. In patients with schizophrenia, LIFC underactivation and left superior temporal gyrus

An fMRI study of semantic processing in men with schizophrenia.

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Kubicki, M; McCarley, R W; Nestor, P G; Huh, T; Kikinis, R; Shenton, M E; Wible, C G

2003-12-01

As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditions. Under the deep, semantic encoding condition, subjects made semantic judgments as to whether the words were abstract or concrete. Under the shallow, nonsemantic encoding condition, subjects made perceptual judgments of the font size (uppercase/lowercase) of the presented words. After performance of the behavioral task, a recognition test was used to assess the depth of processing effect, defined as better performance for semantically encoded words than for perceptually encoded words. For the scanned version only, the words for both conditions were repeated in order to assess repetition-priming effects. Reaction times were assessed in both testing scenarios. Both groups showed the expected depth of processing effect for recognition, and control subjects showed the expected increased activation of the left inferior prefrontal cortex (LIPC) under semantic encoding relative to perceptual encoding conditions as well as repetition priming for semantic conditions only. In contrast, schizophrenics showed similar patterns of fMRI activation regardless of condition. Most striking in relation to controls, patients showed decreased LIFC activation concurrent with increased left superior temporal gyrus activation for semantic encoding versus shallow encoding. Furthermore, schizophrenia subjects did not show the repetition priming effect, either behaviorally or as a decrease in LIPC activity. In patients with schizophrenia, LIFC underactivation and left superior temporal gyrus

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

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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.

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

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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

ERP evidence of distinct processes underlying semantic facilitation and interference in word production.

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Python, Grégoire; Fargier, Raphaël; Laganaro, Marina

2018-02-01

In everyday conversations, we take advantage of lexical-semantic contexts to facilitate speech production, but at the same time, we also have to reduce interference and inhibit semantic competitors. The blocked cyclic naming paradigm (BCNP) has been used to investigate such context effects. Typical results on production latencies showed semantic facilitation (or no effect) during the first presentation cycle, and interference emerging in subsequent cycles. Even if semantic contexts might be just as facilitative as interfering, previous BCNP studies focused on interference, which was interpreted as reflecting lemma selection and self-monitoring processes. Facilitation in the first cycle was rarely considered/analysed, although it potentially informs on word production to the same extent as interference. Here we contrasted the event-related potential (ERP) signatures of both semantic facilitation and interference in a BCNP. ERPs differed between homogeneous and heterogeneous blocks from about 365 msec post picture onset in the first cycle (facilitation) and in an earlier time-window (270 msec post picture onset) in the third cycle (interference). Three different analyses of the ERPs converge towards distinct processes underlying semantic facilitation and interference (post-lexical vs lexical respectively). The loci of semantic facilitation and interference are interpreted in the context of different theoretical frameworks of language production: the post-lexical locus of semantic facilitation involves interactive phonological-semantic processes and/or self-monitoring, whereas the lexical locus of semantic interference is in line with selection through increased lexical competition. Copyright © 2017 Elsevier Ltd. All rights reserved.

Large scale healthcare data integration and analysis using the semantic web.

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Timm, John; Renly, Sondra; Farkash, Ariel

2011-01-01

Healthcare data interoperability can only be achieved when the semantics of the content is well defined and consistently implemented across heterogeneous data sources. Achieving these objectives of interoperability requires the collaboration of experts from several domains. This paper describes tooling that integrates Semantic Web technologies with common tools to facilitate cross-domain collaborative development for the purposes of data interoperability. Our approach is divided into stages of data harmonization and representation, model transformation, and instance generation. We applied our approach on Hypergenes, an EU funded project, where we use our method to the Essential Hypertension disease model using a CDA template. Our domain expert partners include clinical providers, clinical domain researchers, healthcare information technology experts, and a variety of clinical data consumers. We show that bringing Semantic Web technologies into the healthcare interoperability toolkit increases opportunities for beneficial collaboration thus improving patient care and clinical research outcomes.

Age-related reduction of adaptive brain response during semantic integration is associated with gray matter reduction

OpenAIRE

Zhu, Zude; Yang, Fengjun; Li, Dongning; Zhou, Lianjun; Liu, Ying; Zhang, Ying; Chen, Xuezhi

2017-01-01

While aging is associated with increased knowledge, it is also associated with decreased semantic integration. To investigate brain activation changes during semantic integration, a sample of forty-eight 25-75 year-old adults read sentences with high cloze (HC) and low cloze (LC) probability while functional magnetic resonance imaging was conducted. Significant age-related reduction of cloze effect (LC vs. HC) was found in several regions, especially the left middle frontal gyrus (MFG) and ri...

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

Science.gov (United States)

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.

Geospatial semantic web

CERN Document Server

Zhang, Chuanrong; Li, Weidong

2015-01-01

This book covers key issues related to Geospatial Semantic Web, including geospatial web services for spatial data interoperability; geospatial ontology for semantic interoperability; ontology creation, sharing, and integration; querying knowledge and information from heterogeneous data source; interfaces for Geospatial Semantic Web, VGI (Volunteered Geographic Information) and Geospatial Semantic Web; challenges of Geospatial Semantic Web; and development of Geospatial Semantic Web applications. This book also describes state-of-the-art technologies that attempt to solve these problems such as WFS, WMS, RDF, OWL, and GeoSPARQL, and demonstrates how to use the Geospatial Semantic Web technologies to solve practical real-world problems such as spatial data interoperability.

Diagnostic and prognostic role of semantic processing in preclinical Alzheimer's disease.

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Venneri, Annalena; Jahn-Carta, Caroline; Marco, Matteo De; Quaranta, Davide; Marra, Camillo

2018-06-13

Relatively spared during most of the timeline of normal aging, semantic memory shows a subtle yet measurable decline even during the pre-clinical stage of Alzheimer's disease. This decline is thought to reflect early neurofibrillary changes and impairment is detectable using tests of language relying on lexical-semantic abilities. A promising approach is the characterization of semantic parameters such as typicality and age of acquisition of words, and propositional density from verbal output. Seminal research like the Nun Study or the analysis of the linguistic decline of famous writers and politicians later diagnosed with Alzheimer's disease supports the early diagnostic value of semantic processing and semantic memory. Moreover, measures of these skills may play an important role for the prognosis of patients with mild cognitive impairment.

Process Mediation, Execution Monitoring and Recovery for Semantic Web Services

Czech Academy of Sciences Publication Activity Database

Sycara, K.; Vaculín, Roman

2008-01-01

Roč. 31, č. 3 (2008), s. 14-18 ISSN N R&D Projects: GA ČR(CZ) GD201/05/H014; GA MŠk ME08095 Institutional research plan: CEZ:AV0Z10300504 Keywords : process mediation of semantic web services * semantic web services * OWL-S Subject RIV: IN - Informatics, Computer Science

The Semantic Automated Discovery and Integration (SADI Web service Design-Pattern, API and Reference Implementation

Directory of Open Access Journals (Sweden)

Wilkinson Mark D

2011-10-01

Full Text Available Abstract Background The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community. Description SADI - Semantic Automated Discovery and Integration - is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services "stack", SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers. Conclusions SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behaviour we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services

The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation

Science.gov (United States)

2011-01-01

Background The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community. Description SADI - Semantic Automated Discovery and Integration - is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services "stack", SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers. Conclusions SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behaviour we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services can be explored in a manner

The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation.

Science.gov (United States)

Wilkinson, Mark D; Vandervalk, Benjamin; McCarthy, Luke

2011-10-24

The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community. SADI - Semantic Automated Discovery and Integration - is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services "stack", SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers. SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behaviour we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services can be explored in a manner very similar to data housed in

Linguistic expressions and semantic processing a practical approach

CERN Document Server

Butler, Alastair

2015-01-01

This book introduces formal semantics techniques for a natural language processing audience. Methods discussed involve: (i) the denotational techniques used in model-theoretic semantics, which make it possible to determine whether a linguistic expression is true or false with respect to some model of the way things happen to be; and (ii) stages of interpretation, i.e., ways to arrive at meanings by evaluating and converting source linguistic expressions, possibly with respect to contexts, into output (logical) forms that could be used with (i). The book demonstrates that the methods allow w

The use of web ontology languages and other semantic web tools in drug discovery.

Science.gov (United States)

Chen, Huajun; Xie, Guotong

2010-05-01

To optimize drug development processes, pharmaceutical companies require principled approaches to integrate disparate data on a unified infrastructure, such as the web. The semantic web, developed on the web technology, provides a common, open framework capable of harmonizing diversified resources to enable networked and collaborative drug discovery. We survey the state of art of utilizing web ontologies and other semantic web technologies to interlink both data and people to support integrated drug discovery across domains and multiple disciplines. Particularly, the survey covers three major application categories including: i) semantic integration and open data linking; ii) semantic web service and scientific collaboration and iii) semantic data mining and integrative network analysis. The reader will gain: i) basic knowledge of the semantic web technologies; ii) an overview of the web ontology landscape for drug discovery and iii) a basic understanding of the values and benefits of utilizing the web ontologies in drug discovery. i) The semantic web enables a network effect for linking open data for integrated drug discovery; ii) The semantic web service technology can support instant ad hoc collaboration to improve pipeline productivity and iii) The semantic web encourages publishing data in a semantic way such as resource description framework attributes and thus helps move away from a reliance on pure textual content analysis toward more efficient semantic data mining.

Spatial and Semantic Processing between Audition and Vision: An Event-Related Potential Study

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Xiaoxi Chen

2011-10-01

Full Text Available Using a crossmodal priming paradigm, this study investigated how the brain bound the spatial and semantic features in multisensory processing. The visual stimuli (pictures of animals were presented after the auditory stimuli (sounds of animals, and the stimuli from different modalities may match spatially (or semantically or not. Participants were required to detect the head orientation of the visual target (an oddball paradigm. The event-related potentials (ERPs to the visual stimuli was enhanced by spatial attention (150–170 ms irrespectively of semantic information. The early crossmodal attention effect for the visual stimuli was more negative in the spatial-congruent condition than in the spatial-incongruent condition. By contrast, the later effects of spatial ERPs were significant only for the semantic- congruent condition (250–300 ms. These findings indicated that spatial attention modulated early visual processing, and semantic and spatial features were simultaneously used to orient attention and modulate later processing stages.

How "mere" is the mere ownership effect in memory? Evidence for semantic organization processes.

Science.gov (United States)

Englert, Julia; Wentura, Dirk

2016-11-01

Memory is better for items arbitrarily assigned to the self than for items assigned to another person (mere ownership effect, MOE). In a series of six experiments, we investigated the role of semantic processes for the MOE. Following successful replication, we investigated whether the MOE was contingent upon semantic processing: For meaningless stimuli, there was no MOE. Testing for a potential role of semantic elaboration using meaningful stimuli in an encoding task without verbal labels, we found evidence of spontaneous semantic processing irrespective of self- or other-assignment. When semantic organization was manipulated, the MOE vanished if a semantic classification task was added to the self/other assignment but persisted for a perceptual classification task. Furthermore, we found greater clustering of self-assigned than of other-assigned items in free recall. Taken together, these results suggest that the MOE could be based on the organizational principle of a "me" versus "not-me" categorization. Copyright © 2016 Elsevier Inc. All rights reserved.

The Influence of Concreteness of Concepts on the Integration of Novel Words into the Semantic Network.

Science.gov (United States)

Ding, Jinfeng; Liu, Wenjuan; Yang, Yufang

2017-01-01

On the basis of previous studies revealing a processing advantage of concrete words over abstract words, the current study aimed to further explore the influence of concreteness on the integration of novel words into semantic memory with the event related potential (ERP) technique. In the experiment during the learning phase participants read two-sentence contexts and inferred the meaning of novel words. The novel words were two-character non-words in Chinese language. Their meaning was either a concrete or abstract known concept which could be inferred from the contexts. During the testing phase participants performed a lexical decision task in which the learned novel words served as primes for either their corresponding concepts, semantically related or unrelated targets. For the concrete novel words, the semantically related words belonged to the same semantic categories with their corresponding concepts. For the abstract novel words, the semantically related words were synonyms of their corresponding concepts. The unrelated targets were real words which were concrete or abstract for the concrete or abstract novel words respectively. The ERP results showed that the corresponding concepts and the semantically related words elicited smaller N400s than the unrelated words. The N400 effect was not modulated by the concreteness of the concepts. In addition, the concrete corresponding concepts elicited a smaller late positive component (LPC) than the concrete unrelated words. This LPC effect was absent for the abstract words. The results indicate that although both concrete and abstract novel words can be acquired and linked to their related words in the semantic network after a short learning phase, the concrete novel words are learned better. Our findings support the (extended) dual coding theory and broaden our understanding of adult word learning and changes in concept organization.

The Influence of Concreteness of Concepts on the Integration of Novel Words into the Semantic Network

Directory of Open Access Journals (Sweden)

Jinfeng Ding

2017-12-01

Full Text Available On the basis of previous studies revealing a processing advantage of concrete words over abstract words, the current study aimed to further explore the influence of concreteness on the integration of novel words into semantic memory with the event related potential (ERP technique. In the experiment during the learning phase participants read two-sentence contexts and inferred the meaning of novel words. The novel words were two-character non-words in Chinese language. Their meaning was either a concrete or abstract known concept which could be inferred from the contexts. During the testing phase participants performed a lexical decision task in which the learned novel words served as primes for either their corresponding concepts, semantically related or unrelated targets. For the concrete novel words, the semantically related words belonged to the same semantic categories with their corresponding concepts. For the abstract novel words, the semantically related words were synonyms of their corresponding concepts. The unrelated targets were real words which were concrete or abstract for the concrete or abstract novel words respectively. The ERP results showed that the corresponding concepts and the semantically related words elicited smaller N400s than the unrelated words. The N400 effect was not modulated by the concreteness of the concepts. In addition, the concrete corresponding concepts elicited a smaller late positive component (LPC than the concrete unrelated words. This LPC effect was absent for the abstract words. The results indicate that although both concrete and abstract novel words can be acquired and linked to their related words in the semantic network after a short learning phase, the concrete novel words are learned better. Our findings support the (extended dual coding theory and broaden our understanding of adult word learning and changes in concept organization.

Semantic Blogging : Spreading the Semantic Web Meme

OpenAIRE

Cayzer, Steve

2004-01-01

This paper is about semantic blogging, an application of the semantic web to blogging. The semantic web promises to make the web more useful by endowing metadata with machine processable semantics. Blogging is a lightweight web publishing paradigm which provides a very low barrier to entry, useful syndication and aggregation behaviour, a simple to understand structure and decentralized construction of a rich information network. Semantic blogging builds upon the success and clear network valu...

Functional heterogeneity within the default network during semantic processing and speech production.

Directory of Open Access Journals (Sweden)

Mohamed L Seghier

2012-08-01

Full Text Available This fMRI study investigated the functional heterogeneity of the core nodes of the default mode network (DMN during language processing. The core nodes of the DMN were defined as task-induced deactivations over multiple tasks in 94 healthy subjects. We used a factorial design that manipulated different tasks (semantic matching or speech production and stimuli (familiar words and objects or unfamiliar stimuli, alternating with periods of fixation/rest. Our findings revealed several consistent effects in the DMN, namely less deactivations in the left inferior parietal lobule during semantic than perceptual matching in parallel with greater deactivations during semantic matching in anterior subdivisions of the posterior cingulate cortex and the ventromedial prefrontal cortex. This suggests that, when the brain is engaged in effortful semantic tasks, a part of the DMN in the left angular gyrus was less deactivated as five other nodes of the DMN were more deactivated. These five DMN areas, where deactivation was greater for semantic than perceptual matching, were further differentiated because deactivation was greater in (i posterior ventromedial prefrontal cortex for speech production relative to semantic matching, (ii posterior precuneus and posterior cingulate cortex for perceptual processing relative to speech production and (iii right inferior parietal cortex for pictures of objects relative to written words during both naming and semantic decisions. Our results thus highlight that task difficulty alone cannot fully explain the functional variability in task-induced deactivations. Together these results emphasize that core nodes within the DMN are functionally heterogeneous and differentially sensitive to the type of language processing.

Adventures in semantic publishing: exemplar semantic enhancements of a research article.

Directory of Open Access Journals (Sweden)

David Shotton

2009-04-01

Full Text Available 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

Applying semantic web services to enterprise web

OpenAIRE

Hu, Y; Yang, Q P; Sun, X; Wei, P

2008-01-01

Enterprise Web provides a convenient, extendable, integrated platform for information sharing and knowledge management. However, it still has many drawbacks due to complexity and increasing information glut, as well as the heterogeneity of the information processed. Research in the field of Semantic Web Services has shown the possibility of adding higher level of semantic functionality onto the top of current Enterprise Web, enhancing usability and usefulness of resource, enabling decision su...

GIS Data Modeling of a Regional Geological Structure by Integrating Geometric and Semantic Expressions

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HE Handong

2017-08-01

Full Text Available Using GIS, data models of geology via geometric descriptions and expressions are being developed. However, the role played by these data models in terms of the description and expression of geological structure phenomenon is limited. To improve the semantic information in geological GIS data models, this study adopts an object-oriented method that describes and expresses the geometric and semantic features of the geological structure phenomenon using geological objects and designs a data model of regional geological structures by integrating geometry and semantics. Moreover, the study designs a semantic "vocabulary-explanation-graph" method for describing the geological phenomenon of structures. Based on the semantic features of regional geological structures and a linear classification method, it divides the regional geological structure phenomenon into 3 divisions, 10 groups, 33 classes and defines the element set and element class. Moreover, it builds the basic geometric network for geological elements based on the geometric and semantic relations among geological objects. Using the ArcGIS Diagrammer Geodatabase, it considers the regional geological structure of the Ning-Zhen Mountains to verify the data model, and the results indicate a high practicability.

Design and Applications of a GeoSemantic Framework for Integration of Data and Model Resources in Hydrologic Systems

Science.gov (United States)

Elag, M.; Kumar, P.

2016-12-01

Hydrologists today have to integrate resources such as data and models, which originate and reside in multiple autonomous and heterogeneous repositories over the Web. Several resource management systems have emerged within geoscience communities for sharing long-tail data, which are collected by individual or small research groups, and long-tail models, which are developed by scientists or small modeling communities. While these systems have increased the availability of resources within geoscience domains, deficiencies remain due to the heterogeneity in the methods, which are used to describe, encode, and publish information about resources over the Web. This heterogeneity limits our ability to access the right information in the right context so that it can be efficiently retrieved and understood without the Hydrologist's mediation. A primary challenge of the Web today is the lack of the semantic interoperability among the massive number of resources, which already exist and are continually being generated at rapid rates. To address this challenge, we have developed a decentralized GeoSemantic (GS) framework, which provides three sets of micro-web services to support (i) semantic annotation of resources, (ii) semantic alignment between the metadata of two resources, and (iii) semantic mediation among Standard Names. Here we present the design of the framework and demonstrate its application for semantic integration between data and models used in the IML-CZO. First we show how the IML-CZO data are annotated using the Semantic Annotation Services. Then we illustrate how the Resource Alignment Services and Knowledge Integration Services are used to create a semantic workflow among TopoFlow model, which is a spatially-distributed hydrologic model and the annotated data. Results of this work are (i) a demonstration of how the GS framework advances the integration of heterogeneous data and models of water-related disciplines by seamless handling of their semantic

Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System

OpenAIRE

Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang

2017-01-01

Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships betwe...

Semantator: annotating clinical narratives with semantic web ontologies.

Science.gov (United States)

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

2012-01-01

To facilitate clinical research, clinical data needs to be stored in a machine processable and understandable way. Manual annotating clinical data is time consuming. Automatic approaches (e.g., Natural Language Processing systems) have been adopted to convert such data into structured formats; however, the quality of such automatically extracted data may not always be satisfying. In this paper, we propose Semantator, a semi-automatic tool for document annotation with Semantic Web ontologies. With a loaded free text document and an ontology, Semantator supports the creation/deletion of ontology instances for any document fragment, linking/disconnecting instances with the properties in the ontology, and also enables automatic annotation by connecting to the NCBO annotator and cTAKES. By representing annotations in Semantic Web standards, Semantator supports reasoning based upon the underlying semantics of the owl:disjointWith and owl:equivalentClass predicates. We present discussions based on user experiences of using Semantator.

The value of the Semantic Web in the laboratory.

Science.gov (United States)

Frey, Jeremy G

2009-06-01

The Semantic Web is beginning to impact on the wider chemical and physical sciences, beyond the earlier adopted bio-informatics. While useful in large-scale data driven science with automated processing, these technologies can also help integrate the work of smaller scale laboratories producing diverse data. The semantics aid the discovery, reliable re-use of data, provide improved provenance and facilitate automated processing by increased resilience to changes in presentation and reduced ambiguity. The Semantic Web, its tools and collections are not yet competitive with well-established solutions to current problems. It is in the reduced cost of instituting solutions to new problems that the versatility of Semantic Web-enabled data and resources will make their mark once the more general-purpose tools are more available.

Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.

Science.gov (United States)

Chiba, Hirokazu; Nishide, Hiroyo; Uchiyama, Ikuo

2015-01-01

Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis.

Age-related vulnerability in the neural systems supporting semantic processing

Directory of Open Access Journals (Sweden)

Jonathan E Peelle

2013-09-01

Full Text Available Our ability to form abstract representations of objects in semantic memory is crucial to language and thought. The utility of this information relies both on the representations of sensory-motor feature knowledge stored in long-term memory and the executive processes required to retrieve, manipulate, and evaluate this semantic knowledge in a task-relevant manner. These complementary components of semantic memory can be differentially impacted by aging. We investigated semantic processing in normal aging using functional magnetic resonance imaging (fMRI. Young and older adults were asked to judge whether two printed object names match on a particular feature (for example, whether a tomato and strawberry have the same color. The task thus required both retrieval of relevant visual feature knowledge of object concepts and evaluating this information. Objects were drawn from either natural kinds or manufactured objects, and were queried on either color or shape in a factorial design. Behaviorally, all subjects performed well, but older adults could be divided into those whose performance matched that of young adults (better performers and those whose performance was worse (poorer performers. All subjects activated several cortical regions while performing this task, including bilateral inferior and lateral temporal cortex and left frontal and prefrontal cortex. Better performing older adults showed increased overall activity in bilateral premotor cortex and left lateral occipital cortex compared to young adults, and increased activity in these brain regions relative to poorer performing older adults who also showed gray matter atrophy in premotor cortex. These findings highlight the contribution of domain-general executive processing brain regions to semantic memory, and illustrate differences in how these regions are recruited in healthy older adults.

Learning new vocabulary during childhood: effects of semantic training on lexical consolidation and integration.

Science.gov (United States)

Henderson, Lisa; Weighall, Anna; Gaskell, Gareth

2013-11-01

Research suggests that word learning is an extended process, with offline consolidation crucial for the strengthening of new lexical representations and their integration with existing lexical knowledge (as measured by engagement in lexical competition). This supports a dual memory systems account, in which new information is initially sparsely encoded separately from existing knowledge and integrated with long-term memory over time. However, previous studies of this type exploited unnatural learning contexts, involving fictitious words in the absence of word meaning. In this study, 5- to 9-year-old children learned real science words (e.g., hippocampus) with or without semantic information. Children in both groups were slower to detect pauses in familiar competitor words (e.g., hippopotamus) relative to control words 24h after training but not immediately, confirming that offline consolidation is required before new words are integrated with the lexicon and engage in lexical competition. Children recalled more new words 24h after training than immediately (with similar improvements shown for the recall and recognition of new word meanings); however, children who were exposed to the meanings during training showed further improvements in recall after 1 week and outperformed children who were not exposed to meanings. These findings support the dual memory systems account of vocabulary acquisition and suggest that the association of a new phonological form with semantic information is critical for the development of stable lexical representations. Copyright © 2013 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Semantic orchestration of image processing services for environmental analysis

Science.gov (United States)

Ranisavljević, Élisabeth; Devin, Florent; Laffly, Dominique; Le Nir, Yannick

2013-09-01

In order to analyze environmental dynamics, a major process is the classification of the different phenomena of the site (e.g. ice and snow for a glacier). When using in situ pictures, this classification requires data pre-processing. Not all the pictures need the same sequence of processes depending on the disturbances. Until now, these sequences have been done manually, which restricts the processing of large amount of data. In this paper, we present how to realize a semantic orchestration to automate the sequencing for the analysis. It combines two advantages: solving the problem of the amount of processing, and diversifying the possibilities in the data processing. We define a BPEL description to express the sequences. This BPEL uses some web services to run the data processing. Each web service is semantically annotated using an ontology of image processing. The dynamic modification of the BPEL is done using SPARQL queries on these annotated web services. The results obtained by a prototype implementing this method validate the construction of the different workflows that can be applied to a large number of pictures.

The Influence of Concreteness of Concepts on the Integration of Novel Words into the Semantic Network

OpenAIRE

Ding, Jinfeng; Liu, Wenjuan; Yang, Yufang

2017-01-01

On the basis of previous studies revealing a processing advantage of concrete words over abstract words, the current study aimed to further explore the influence of concreteness on the integration of novel words into semantic memory with the event related potential (ERP) technique. In the experiment during the learning phase participants read two-sentence contexts and inferred the meaning of novel words. The novel words were two-character non-words in Chinese language. Their meaning was eithe...

Arabic web pages clustering and annotation using semantic class features

Directory of Open Access Journals (Sweden)

Hanan M. Alghamdi

2014-12-01

Full Text Available To effectively manage the great amount of data on Arabic web pages and to enable the classification of relevant information are very important research problems. Studies on sentiment text mining have been very limited in the Arabic language because they need to involve deep semantic processing. Therefore, in this paper, we aim to retrieve machine-understandable data with the help of a Web content mining technique to detect covert knowledge within these data. We propose an approach to achieve clustering with semantic similarities. This approach comprises integrating k-means document clustering with semantic feature extraction and document vectorization to group Arabic web pages according to semantic similarities and then show the semantic annotation. The document vectorization helps to transform text documents into a semantic class probability distribution or semantic class density. To reach semantic similarities, the approach extracts the semantic class features and integrates them into the similarity weighting schema. The quality of the clustering result has evaluated the use of the purity and the mean intra-cluster distance (MICD evaluation measures. We have evaluated the proposed approach on a set of common Arabic news web pages. We have acquired favorable clustering results that are effective in minimizing the MICD, expanding the purity and lowering the runtime.

An explicit semantic relatedness measure based on random walk

Directory of Open Access Journals (Sweden)

HU Sihui

2016-10-01

Full Text Available The semantic relatedness calculation of open domain knowledge network is a significant issue.In this paper,pheromone strategy is drawn from the thought of ant colony algorithm and is integrated into the random walk which is taken as the basic framework of calculating the semantic relatedness degree.The pheromone distribution is taken as a criterion of determining the tightness degree of semantic relatedness.A method of calculating semantic relatedness degree based on random walk is proposed and the exploration process of calculating the semantic relatedness degree is presented in a dominant way.The method mainly contains Path Select Model(PSM and Semantic Relatedness Computing Model(SRCM.PSM is used to simulate the path selection of ants and pheromone release.SRCM is used to calculate the semantic relatedness by utilizing the information returned by ants.The result indicates that the method could complete semantic relatedness calculation in linear complexity and extend the feasible strategy of semantic relatedness calculation.

Brain network of semantic integration in sentence reading: insights from independent component analysis and graph theoretical analysis.

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Ye, Zheng; Doñamayor, Nuria; Münte, Thomas F

2014-02-01

A set of cortical and sub-cortical brain structures has been linked with sentence-level semantic processes. However, it remains unclear how these brain regions are organized to support the semantic integration of a word into sentential context. To look into this issue, we conducted a functional magnetic resonance imaging (fMRI) study that required participants to silently read sentences with semantically congruent or incongruent endings and analyzed the network properties of the brain with two approaches, independent component analysis (ICA) and graph theoretical analysis (GTA). The GTA suggested that the whole-brain network is topologically stable across conditions. The ICA revealed a network comprising the supplementary motor area (SMA), left inferior frontal gyrus, left middle temporal gyrus, left caudate nucleus, and left angular gyrus, which was modulated by the incongruity of sentence ending. Furthermore, the GTA specified that the connections between the left SMA and left caudate nucleus as well as that between the left caudate nucleus and right thalamus were stronger in response to incongruent vs. congruent endings. Copyright © 2012 Wiley Periodicals, Inc.

Semantic Enhancement for Enterprise Data Management

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Ma, Li; Sun, Xingzhi; Cao, Feng; Wang, Chen; Wang, Xiaoyuan; Kanellos, Nick; Wolfson, Dan; Pan, Yue

Taking customer data as an example, the paper presents an approach to enhance the management of enterprise data by using Semantic Web technologies. Customer data is the most important kind of core business entity a company uses repeatedly across many business processes and systems, and customer data management (CDM) is becoming critical for enterprises because it keeps a single, complete and accurate record of customers across the enterprise. Existing CDM systems focus on integrating customer data from all customer-facing channels and front and back office systems through multiple interfaces, as well as publishing customer data to different applications. To make the effective use of the CDM system, this paper investigates semantic query and analysis over the integrated and centralized customer data, enabling automatic classification and relationship discovery. We have implemented these features over IBM Websphere Customer Center, and shown the prototype to our clients. We believe that our study and experiences are valuable for both Semantic Web community and data management community.

Semantic Integration as a Boundary Condition on Inhibitory Processes in Episodic Retrieval

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Goodmon, Leilani B.; Anderson, Michael C.

2011-01-01

Recalling an experience often impairs the later retention of related traces, a phenomenon known as retrieval-induced forgetting (RIF). Research has shown that episodic associations protect competing memories from RIF (Anderson & McCulloch, 1999). We report 4 experiments that examined whether semantic associations also protect against RIF. In…

The effect of a prospected reward on semantic processing : An N400 EEG study

NARCIS (Netherlands)

van der Ven, Sanne H. G.; van Touw, Sven A. C.; van Hoogmoed, Anne H.; Janssen, Eva M.; Leseman, Paul P. M.

2016-01-01

Promised rewards are often used in education to stimulate learning behaviour. The present study tested whether a reward prospect affects semantic processing and recall of learned materials. Thirty-nine females participated in an electroencephalogram (EEG) task measuring semantic processing using the

A dual contribution to the involuntary semantic processing of unexpected spoken words.

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Parmentier, Fabrice B R; Turner, Jacqueline; Perez, Laura

2014-02-01

Sounds are a major cause of distraction. Unexpected to-be-ignored auditory stimuli presented in the context of an otherwise repetitive acoustic background ineluctably break through selective attention and distract people from an unrelated visual task (deviance distraction). This involuntary capture of attention by deviant sounds has been hypothesized to trigger their semantic appraisal and, in some circumstances, interfere with ongoing performance, but it remains unclear how such processing compares with the automatic processing of distractors in classic interference tasks (e.g., Stroop, flanker, Simon tasks). Using a cross-modal oddball task, we assessed the involuntary semantic processing of deviant sounds in the presence and absence of deviance distraction. The results revealed that some involuntary semantic analysis of spoken distractors occurs in the absence of deviance distraction but that this processing is significantly greater in its presence. We conclude that the automatic processing of spoken distractors reflects 2 contributions, one that is contingent upon deviance distraction and one that is independent from it.

UML 2 Semantics and Applications

CERN Document Server

Lano, Kevin

2009-01-01

A coherent and integrated account of the leading UML 2 semantics work and the practical applications of UML semantics development With contributions from leading experts in the field, the book begins with an introduction to UML and goes on to offer in-depth and up-to-date coverage of: The role of semantics Considerations and rationale for a UML system model Definition of the UML system model UML descriptive semantics Axiomatic semantics of UML class diagrams The object constraint language Axiomatic semantics of state machines A coalgebraic semantic framework for reasoning about interaction des

Semantics and analysis of business process models in BPMN

NARCIS (Netherlands)

Dijkman, R.M.; Dumas, M.; Ouyang, C.

2008-01-01

The Business Process Modelling Notation (BPMN) is a standard for capturing business processes in the early phases of systems development. The mix of constructs found in BPMN makes it possible to create models with semantic errors. Such errors are especially serious, because errors in the early

Semantic dysfunction in women with schizotypal personality disorder.

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Niznikiewicz, Margaret A; Shenton, Martha E; Voglmaier, Martina; Nestor, Paul G; Dickey, Chandlee C; Frumin, Melissa; Seidman, Larry J; Allen, Christopher G; McCarley, Robert W

2002-10-01

This study examined whether early or late processes in semantic networks were abnormal in women with a diagnosis of schizotypal personality disorder. The N400 component of the EEG event-related potentials was used as a probe of semantic processes. Word pairs were presented with short and long stimulus-onset asynchronies to investigate, respectively, early and late semantic processes in 16 women with schizotypal personality disorder and 15 normal female comparison subjects. Event-related potentials were recorded in response to the last words in a pair. With the short stimulus-onset asynchrony, the N400 amplitude was less negative in the schizotypal personality disorder group than in the normal comparison group. No group differences were found with the long stimulus-onset asynchrony. The finding of a less negative than normal N400 amplitude with the short stimulus-onset asynchrony in women with schizotypal personality disorder supports the hypothesis that persons with this disorder evince an overactivation of semantic networks. The absence of group differences with the long stimulus-onset asynchrony, which is primarily sensitive to processes involved in context integration, suggests that in this group of schizotypal personality disorder subjects, additional demands on working memory may be necessary to bring out the semantic dysfunction.

Using ontology-based semantic similarity to facilitate the article screening process for systematic reviews.

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Ji, Xiaonan; Ritter, Alan; Yen, Po-Yin

2017-05-01

Systematic Reviews (SRs) are utilized to summarize evidence from high quality studies and are considered the preferred source of evidence-based practice (EBP). However, conducting SRs can be time and labor intensive due to the high cost of article screening. In previous studies, we demonstrated utilizing established (lexical) article relationships to facilitate the identification of relevant articles in an efficient and effective manner. Here we propose to enhance article relationships with background semantic knowledge derived from Unified Medical Language System (UMLS) concepts and ontologies. We developed a pipelined semantic concepts representation process to represent articles from an SR into an optimized and enriched semantic space of UMLS concepts. Throughout the process, we leveraged concepts and concept relations encoded in biomedical ontologies (SNOMED-CT and MeSH) within the UMLS framework to prompt concept features of each article. Article relationships (similarities) were established and represented as a semantic article network, which was readily applied to assist with the article screening process. We incorporated the concept of active learning to simulate an interactive article recommendation process, and evaluated the performance on 15 completed SRs. We used work saved over sampling at 95% recall (WSS95) as the performance measure. We compared the WSS95 performance of our ontology-based semantic approach to existing lexical feature approaches and corpus-based semantic approaches, and found that we had better WSS95 in most SRs. We also had the highest average WSS95 of 43.81% and the highest total WSS95 of 657.18%. We demonstrated using ontology-based semantics to facilitate the identification of relevant articles for SRs. Effective concepts and concept relations derived from UMLS ontologies can be utilized to establish article semantic relationships. Our approach provided a promising performance and can easily apply to any SR topics in the

A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare.

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Mezghani, Emna; Exposito, Ernesto; Drira, Khalil; Da Silveira, Marcos; Pruski, Cédric

2015-12-01

Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients' health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The diversity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the "Knowledge as a Service" approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status.

Fine-coarse semantic processing in schizophrenia: a reversed pattern of hemispheric dominance.

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Zeev-Wolf, Maor; Goldstein, Abraham; Levkovitz, Yechiel; Faust, Miriam

2014-04-01

Left lateralization for language processing is a feature of neurotypical brains. In individuals with schizophrenia, lack of left lateralization is associated with the language impairments manifested in this population. Beeman׳s fine-coarse semantic coding model asserts left hemisphere specialization in fine (i.e., conventionalized) semantic coding and right hemisphere specialization in coarse (i.e., non-conventionalized) semantic coding. Applying this model to schizophrenia would suggest that language impairments in this population are a result of greater reliance on coarse semantic coding. We investigated this hypothesis and examined whether a reversed pattern of hemispheric involvement in fine-coarse semantic coding along the time course of activation could be detected in individuals with schizophrenia. Seventeen individuals with schizophrenia and 30 neurotypical participants were presented with two word expressions of four types: literal, conventional metaphoric, unrelated (exemplars of fine semantic coding) and novel metaphoric (an exemplar of coarse semantic coding). Expressions were separated by either a short (250 ms) or long (750 ms) delay. Findings indicate that whereas during novel metaphor processing, controls displayed a left hemisphere advantage at 250 ms delay and right hemisphere advantage at 750 ms, individuals with schizophrenia displayed the opposite. For conventional metaphoric and unrelated expressions, controls showed left hemisphere advantage across times, while individuals with schizophrenia showed a right hemisphere advantage. Furthermore, whereas individuals with schizophrenia were less accurate than control at judging literal, conventional metaphoric and unrelated expressions they were more accurate when judging novel metaphors. Results suggest that individuals with schizophrenia display a reversed pattern of lateralization for semantic coding which causes them to rely more heavily on coarse semantic coding. Thus, for individuals with

Applications and methods utilizing the Simple Semantic Web Architecture and Protocol (SSWAP for bioinformatics resource discovery and disparate data and service integration

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Nelson Rex T

2010-06-01

Full Text Available Abstract Background Scientific data integration and computational service discovery are challenges for the bioinformatic community. This process is made more difficult by the separate and independent construction of biological databases, which makes the exchange of data between information resources difficult and labor intensive. A recently described semantic web protocol, the Simple Semantic Web Architecture and Protocol (SSWAP; pronounced "swap" offers the ability to describe data and services in a semantically meaningful way. We report how three major information resources (Gramene, SoyBase and the Legume Information System [LIS] used SSWAP to semantically describe selected data and web services. Methods We selected high-priority Quantitative Trait Locus (QTL, genomic mapping, trait, phenotypic, and sequence data and associated services such as BLAST for publication, data retrieval, and service invocation via semantic web services. Data and services were mapped to concepts and categories as implemented in legacy and de novo community ontologies. We used SSWAP to express these offerings in OWL Web Ontology Language (OWL, Resource Description Framework (RDF and eXtensible Markup Language (XML documents, which are appropriate for their semantic discovery and retrieval. We implemented SSWAP services to respond to web queries and return data. These services are registered with the SSWAP Discovery Server and are available for semantic discovery at http://sswap.info. Results A total of ten services delivering QTL information from Gramene were created. From SoyBase, we created six services delivering information about soybean QTLs, and seven services delivering genetic locus information. For LIS we constructed three services, two of which allow the retrieval of DNA and RNA FASTA sequences with the third service providing nucleic acid sequence comparison capability (BLAST. Conclusions The need for semantic integration technologies has preceded

Intelligent query processing for semantic mediation of information systems

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Saber Benharzallah

2011-11-01

Full Text Available We propose an intelligent and an efficient query processing approach for semantic mediation of information systems. We propose also a generic multi agent architecture that supports our approach. Our approach focuses on the exploitation of intelligent agents for query reformulation and the use of a new technology for the semantic representation. The algorithm is self-adapted to the changes of the environment, offers a wide aptitude and solves the various data conflicts in a dynamic way; it also reformulates the query using the schema mediation method for the discovered systems and the context mediation for the other systems.

Oscillatory neuronal activity reflects lexical-semantic feature integration within and across sensory modalities in distributed cortical networks.

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van Ackeren, Markus J; Schneider, Till R; Müsch, Kathrin; Rueschemeyer, Shirley-Ann

2014-10-22

Research from the previous decade suggests that word meaning is partially stored in distributed modality-specific cortical networks. However, little is known about the mechanisms by which semantic content from multiple modalities is integrated into a coherent multisensory representation. Therefore we aimed to characterize differences between integration of lexical-semantic information from a single modality compared with two sensory modalities. We used magnetoencephalography in humans to investigate changes in oscillatory neuronal activity while participants verified two features for a given target word (e.g., "bus"). Feature pairs consisted of either two features from the same modality (visual: "red," "big") or different modalities (auditory and visual: "red," "loud"). The results suggest that integrating modality-specific features of the target word is associated with enhanced high-frequency power (80-120 Hz), while integrating features from different modalities is associated with a sustained increase in low-frequency power (2-8 Hz). Source reconstruction revealed a peak in the anterior temporal lobe for low-frequency and high-frequency effects. These results suggest that integrating lexical-semantic knowledge at different cortical scales is reflected in frequency-specific oscillatory neuronal activity in unisensory and multisensory association networks. Copyright © 2014 the authors 0270-6474/14/3314318-06$15.00/0.

Semantic processing of unattended parafoveal words.

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Di Pace, E; Longoni, A M; Zoccolotti, P

1991-08-01

The influence that a context word presented either foveally or parafoveally, may exert on the processing of a subsequent target word was studied in a semantic decision task. Fourteen subjects participated in the experiment. They were presented with word-nonword pairs (prime). One member of the pair (which the subjects had to attend to) appeared centrally, the other parafoveally. The prime was followed by a target at two inter-stimulus intervals (ISI; 200 and 2000 msec). The word stimulus of the pair could be semantically related or unrelated to the target. The subjects' task was to classify the target as animal or not animal by pressing one of two buttons as quickly as possible. When the target word was semantically associated with the foveal (attended) word the reaction times were faster for both ISIs; when it was associated with the parafoveal (unattended) word in the prime pair, there were facilitatory effects only in the short ISI condition. A second experiment was run in order to evaluate the possibility that the obtained results were due to identification of the parafoveal stimulus. The same prime-target pairs of experiment 1 (without the target stimuli) were used. The prime-target pairs were presented to fourteen subjects who were requested to name the foveal (attended) stimulus and subsequently, if possible, the parafoveal (unattended) one. Even in this condition, percentage of identification of the unattended word was only 15%, suggesting that previous findings were not due to identification of unattended stimuli. Results are discussed in relation to Posner and Snyder's (1975) dual coding theory.

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

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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.

The MMI Semantic Framework: Rosetta Stones for Earth Sciences

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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

Interoperable cross-domain semantic and geospatial framework for automatic change detection

Science.gov (United States)

Kuo, Chiao-Ling; Hong, Jung-Hong

2016-01-01

With the increasingly diverse types of geospatial data established over the last few decades, semantic interoperability in integrated applications has attracted much interest in the field of Geographic Information System (GIS). This paper proposes a new strategy and framework to process cross-domain geodata at the semantic level. This framework leverages the semantic equivalence of concepts between domains through bridge ontology and facilitates the integrated use of different domain data, which has been long considered as an essential superiority of GIS, but is impeded by the lack of understanding about the semantics implicitly hidden in the data. We choose the task of change detection to demonstrate how the introduction of ontology concept can effectively make the integration possible. We analyze the common properties of geodata and change detection factors, then construct rules and summarize possible change scenario for making final decisions. The use of topographic map data to detect changes in land use shows promising success, as far as the improvement of efficiency and level of automation is concerned. We believe the ontology-oriented approach will enable a new way for data integration across different domains from the perspective of semantic interoperability, and even open a new dimensionality for the future GIS.

A semantic web approach applied to integrative bioinformatics experimentation: a biological use case with genomics data.

NARCIS (Netherlands)

Post, L.J.G.; Roos, M.; Marshall, M.S.; van Driel, R.; Breit, T.M.

2007-01-01

The numerous public data resources make integrative bioinformatics experimentation increasingly important in life sciences research. However, it is severely hampered by the way the data and information are made available. The semantic web approach enhances data exchange and integration by providing

An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework

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Gao, Wenlong

2012-01-01

The ontology approach has been accepted as a very promising approach to semantic integration today. However, because of the diversity of focuses and its various connections to other research domains, the core concepts, theoretical and technical approaches, and research areas of this domain still remain unclear. Such ambiguity makes it difficult to…

Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration.

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Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris

2016-07-08

This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) BACKGROUND: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) METHODS: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) RESULTS: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) CONCLUSION: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database.

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

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Keller, Richard M.; Ranjan, Shubha; Wei, Mie; Eshow, Michelle

2016-01-01

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

Rigidity, Chaos and Integration: Hemispheric Interaction and Individual Differences in Metaphor Comprehension

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Miriam eFaust

2014-07-01

Full Text Available Neurotypical individuals cope flexibly with the full range of semantic relations expressed in human language, including metaphoric relations. This impressive semantic ability may be associated with distinct and flexible patterns of hemispheric interaction, including higher right hemisphere (RH involvement for processing novel metaphors. However, this ability may be impaired in specific clinical conditions, such as Asperger syndrome and schizophrenia. The impaired semantic processing is accompanied by different patterns of hemispheric interaction during semantic processing, showing either reduced (in Asperger or excessive (in schizophrenia RH involvement. This paper interprets these individual differences using the terms Rigidity, Chaos and Integration, which describe patterns of semantic memory network states that either lead to semantic well-being or are disruptive of it. We argue that these semantic network states lie on a rigidity-chaos semantic continuum. We define these terms via network science terminology and provide network, cognitive and neural evidence to support our claim. This continuum includes LH hyper-rigid semantic memory state on one end (e.g., in persons with Asperger syndrome, and RH chaotic and over-flexible semantic memory state on the other end (e.g., in persons with schizophrenia. In between these two extremes lie different states of semantic memory structure which are related to individual differences in semantic creativity. We suggest that efficient semantic processing is achieved by semantic integration, a balance between semantic rigidity and semantic chaos. Such integration is achieved via intra-hemispheric communication. However, impairments to this well-balanced and integrated pattern of hemispheric interaction, e.g., when one hemisphere dominates the other, may lead to either semantic rigidity or semantic chaos, moving away from semantic integration and thus impairing the processing of metaphoric language.

The Neural Correlates of the Body-Object Interaction Effect in Semantic Processing

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Ian Scott Hargreaves

2012-02-01

Full Text Available The semantic richness dimension referred to as body-object interaction (BOI measures perceptions of the ease with which people can physically interact with words’ referents. Previous studies have shown facilitated lexical and semantic processing for words rated high in BOI (e.g., belt than for words rated low in BOI (e.g., sun (e.g., Siakaluk, Pexman, Sears, Wilson, Locheed, & Owen, 2008b. These BOI effects have been taken as evidence that embodied information is relevant to word recognition. However, to date there is no evidence linking BOI manipulations to differences in the utilization of perceptual or sensorimotor areas of the brain. The current study used event-related fMRI to examine the neural correlates of BOI in a semantic categorization task (SCT. Sixteen healthy adults participated. Results showed that high BOI words were associated with activation in the left inferior parietal lobule (supramarginal gyrus, BA 40, a sensory association area involved in kinesthetic memory. These results provide evidence that the BOI dimension captures sensorimotor information, and that this contributes to semantic processing.

The Process Mediation Framework for Semantic Web Services

Czech Academy of Sciences Publication Activity Database

Vaculín, Roman; Neruda, Roman

2009-01-01

Roč. 3, č. 1 (2009), s. 27-58 ISSN 1746-1375 R&D Projects: GA MŠk ME08095; GA AV ČR 1ET100300517 Institutional research plan: CEZ:AV0Z10300504 Keywords : process mediation * OWL-S * semantic web services * adapter synthesis Subject RIV: IN - Informatics, Computer Science

Testing for a cultural influence on reading for meaning in the developing brain: the neural basis of semantic processing in Chinese children

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Tai-Li Chou

2009-11-01

Full Text Available Functional magnetic resonance imaging (fMRI was used to explore the neural correlates of semantic judgments in a group of 8- to 15-year-old Chinese children. Participants were asked to indicate if pairs of Chinese characters presented visually were related in meaning. The related pairs were arranged in a continuous variable according to association strength. Pairs of characters with weaker semantic association elicited greater activation in the mid ventral region (BA 45 of left inferior frontal gyrus, suggesting increased demands on the process of selecting appropriate semantic features. By contrast, characters with stronger semantic association elicited greater activation in left inferior parietal lobule (BA 39, suggesting stronger integration of highly related features. In addition, there was a developmental increase, similar to previously reported findings in English, in left posterior middle temporal gyrus (BA 21, suggesting that older children have more elaborated semantic representations. There were additional age-related increases in the posterior region of left inferior parietal lobule and in the ventral regions of left inferior frontal gyrus, suggesting that reading acquisition relies more on the mapping from orthography to semantics in Chinese children as compared to previously reported findings in English.

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

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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

Semantic Web status model

CSIR Research Space (South Africa)

Gerber, AJ

2006-06-01

Full Text Available Semantic Web application areas are experiencing intensified interest due to the rapid growth in the use of the Web, together with the innovation and renovation of information content technologies. The Semantic Web is regarded as an integrator across...

Efecto de la riqueza semántica en distintos niveles del procesamiento léxico-semántico (Semantic richness effect at different levels of lexical-semantic processing

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Mauro Fragapane

2017-08-01

Full Text Available Semantic richness is a multidimensional construct that refers to the extent of variability of information associated with the meaning of a word. The Number of Features (NoF is a dimension of semantic richness that has been shown to have a major influence on lexical and semantic processing. Several studies have shown that concepts with a higher NoF allow faster lexical processing than those with a lower NoF. The current study is the first to use a NoF measure based on norms obtained from a sample of Spanish-speaking participants. The aim was to study the effect of this variable in visual word recognition. The sample included 90 young native Spanish-speaking adults. Three tasks were administered that require access to different lexico-semantic levels: lexical decision, concreteness semantic categorization (concrete/abstract, and domain semantic categorization (living/non-living. A semantic richness effect was found in lexical decision and domain semantic categorization tasks, with greater effect in the latter task. Results are interpreted within the framework of the General Domain Interactive Activation model.

Self-referential processing is distinct from semantic elaboration: evidence from long-term memory effects in a patient with amnesia and semantic impairments.

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Sui, Jie; Humphreys, Glyn W

2013-11-01

We report data demonstrating that self-referential encoding facilitates memory performance in the absence of effects of semantic elaboration in a severely amnesic patient also suffering semantic problems. In Part 1, the patient, GA, was trained to associate items with the self or a familiar other during the encoding phase of a memory task (self-ownership decisions in Experiment 1 and self-evaluation decisions in Experiment 2). Tests of memory showed a consistent self-reference advantage, relative to a condition where the reference was another person in both experiments. The pattern of the self-reference advantage was similar to that in healthy controls. In Part 2 we demonstrate that GA showed minimal effects of semantic elaboration on memory for items he semantically classified, compared with items subject to physical size decisions; in contrast, healthy controls demonstrated enhanced memory performance after semantic relative to physical encoding. The results indicate that self-referential encoding, not semantic elaboration, improves memory in amnesia. Self-referential processing may provide a unique scaffold to help improve learning in amnesic cases. Copyright © 2013 Elsevier Ltd. All rights reserved.

Applied Semantic Web Technologies

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Sugumaran, Vijayan

2011-01-01

The rapid advancement of semantic web technologies, along with the fact that they are at various levels of maturity, has left many practitioners confused about the current state of these technologies. Focusing on the most mature technologies, Applied Semantic Web Technologies integrates theory with case studies to illustrate the history, current state, and future direction of the semantic web. It maintains an emphasis on real-world applications and examines the technical and practical issues related to the use of semantic technologies in intelligent information management. The book starts with

Semantic Web Technologies and Big Data Infrastructures: SPARQL Federated Querying of Heterogeneous Big Data Stores

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Konstantopoulos, Stasinos; Charalambidis, Angelos; Mouchakis, Giannis; Troumpoukis, Antonis; Jakobitsch, Jürgen; Karkaletsis, Vangelis

2016-01-01

The ability to cross-link large scale data with each other and with structured Semantic Web data, and the ability to uniformly process Semantic Web and other data adds value to both the Semantic Web and to the Big Data community. This paper presents work in progress towards integrating Big Data infrastructures with Semantic Web technologies, allowing for the cross-linking and uniform retrieval of data stored in both Big Data infrastructures and Semantic Web data. The technical challenges invo...

Effect of aging, education, reading and writing, semantic processing and depression symptoms on verbal fluency

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André Luiz Moraes

2013-12-01

Full Text Available Verbal fluency tasks are widely used in (clinical neuropsychology to evaluate components of executive functioning and lexical-semantic processing (linguistic and semantic memory. Performance in those tasks may be affected by several variables, such as age, education and diseases. This study investigated whether aging, education, reading and writing frequency, performance in semantic judgment tasks and depression symptoms predict the performance in unconstrained, phonemic and semantic fluency tasks. This study sample comprised 260 healthy adults aged 19 to 75 years old. The Pearson correlation coefficient and multiple regression models were used for data analysis. The variables under analysis were associated in different ways and had different levels of contribution according to the type of verbal fluency task. Education had the greatest effect on verbal fluency tasks. There was a greater effect of age on semantic fluency than on phonemic tasks. The semantic judgment tasks predicted the verbal fluency performance alone or in combination with other variables. These findings corroborate the importance of education in cognition supporting the hypothesis of a cognitive reserve and confirming the contribution of lexical-semantic processing to verbal fluency.

Semantically Interoperable XML Data.

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

2013-09-01

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.

Semantically Interoperable XML Data

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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

Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration

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Min-Jung Yoo

2016-07-01

Full Text Available This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT. The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI and Open Data Format (O-DF, which ensures data communication. (1 Background: Based on an existing product lifecycle management (PLM methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2 Methods: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA uses the message format as a common protocol of product-service lifecycle data transfer; (3 Results: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4 Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5 Conclusion: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF database.

Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration

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Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris

2016-01-01

This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) Background: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) Methods: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) Results: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) Conclusion: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database. PMID:27399717

Semantic web data warehousing for caGrid.

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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.

From perceptual to lexico-semantic analysis--cortical plasticity enabling new levels of processing.

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Schlaffke, Lara; Rüther, Naima N; Heba, Stefanie; Haag, Lauren M; Schultz, Thomas; Rosengarth, Katharina; Tegenthoff, Martin; Bellebaum, Christian; Schmidt-Wilcke, Tobias

2015-11-01

Certain kinds of stimuli can be processed on multiple levels. While the neural correlates of different levels of processing (LOPs) have been investigated to some extent, most of the studies involve skills and/or knowledge already present when performing the task. In this study we specifically sought to identify neural correlates of an evolving skill that allows the transition from perceptual to a lexico-semantic stimulus analysis. Eighteen participants were trained to decode 12 letters of Morse code that were presented acoustically inside and outside of the scanner environment. Morse code was presented in trains of three letters while brain activity was assessed with fMRI. Participants either attended to the stimulus length (perceptual analysis), or evaluated its meaning distinguishing words from nonwords (lexico-semantic analysis). Perceptual and lexico-semantic analyses shared a mutual network comprising the left premotor cortex, the supplementary motor area (SMA) and the inferior parietal lobule (IPL). Perceptual analysis was associated with a strong brain activation in the SMA and the superior temporal gyrus bilaterally (STG), which remained unaltered from pre and post training. In the lexico-semantic analysis post learning, study participants showed additional activation in the left inferior frontal cortex (IFC) and in the left occipitotemporal cortex (OTC), regions known to be critically involved in lexical processing. Our data provide evidence for cortical plasticity evolving with a learning process enabling the transition from perceptual to lexico-semantic stimulus analysis. Importantly, the activation pattern remains task-related LOP and is thus the result of a decision process as to which LOP to engage in. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control

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Jude Adekunle Adeleke

2017-04-01

Full Text Available Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control.

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Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka

2017-04-09

Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

Lexical-Semantic Processing and Reading: Relations between Semantic Priming, Visual Word Recognition and Reading Comprehension

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Nobre, Alexandre de Pontes; de Salles, Jerusa Fumagalli

2016-01-01

The aim of this study was to investigate relations between lexical-semantic processing and two components of reading: visual word recognition and reading comprehension. Sixty-eight children from private schools in Porto Alegre, Brazil, from 7 to 12 years, were evaluated. Reading was assessed with a word/nonword reading task and a reading…

Semantic, syntactic, and phonological processing of written words in adult developmental dyslexic readers: an event-related brain potential study

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Johannes Sönke

2007-07-01

Full Text Available Abstract Background The present study used event-related brain potentials to investigate semantic, phonological and syntactic processes in adult German dyslexic and normal readers in a word reading task. Pairs of German words were presented one word at a time. Subjects had to perform a semantic judgment task (house – window; are they semantically related?, a rhyme judgment task (house – mouse; do they rhyme? and a gender judgment task (das – Haus [the – house]; is the gender correct? [in German, house has a neutral gender: das Haus]. Results Normal readers responded faster compared to dyslexic readers in all three tasks. Onset latencies of the N400 component were delayed in dyslexic readers in the rhyme judgment and in the gender judgment task, but not in the semantic judgment task. N400 and the anterior negativity peak amplitudes did not differ between the two groups. However, the N400 persisted longer in the dyslexic group in the rhyme judgment and in the semantic judgment tasks. Conclusion These findings indicate that dyslexics are phonologically impaired (delayed N400 in the rhyme judgment task but that they also have difficulties in other, non-phonological aspects of reading (longer response times, longer persistence of the N400. Specifically, semantic and syntactic integration seem to require more effort for dyslexic readers and take longer irrespective of the reading task that has to be performed.

Semantic Congruency in Audiovisual Integration as Revealed by the Continuous Flash Suppression Paradigm

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Yung-Hao Yang

2011-10-01

Full Text Available Despite several demonstrations of crossmodal semantic-congruency effect, it remains controversial as to whether it is a genuine perceptual phenomenon or instead it actually results from post-perceptual response bias such as decision or strategies (de Gelder and Bertelson, 2003. Here we combine the invisible stimuli with sounds to exclude the participants' awareness of the relation between visual and auditory stimuli. We render the visual events invisible by adopting the continuous flash suppression paradigm (Tsuchiya and Koch, 2005 in which the dynamic high-contrast visual patches were presented in one eye to suppress the target that was presented in the other eye. The semantic congruency between visual and auditory stimuli was manipulated and participants had to detect any parts of visual target. The results showed that the time needed to detect the visual target (ie, the release from suppression was faster when it was accompanied by a semantically congruent sound than with an incongruent one. This study therefore demonstrates genuine multisensory integration at the semantic level. Furthermore, it also extends from previous studies with neglect blindsight patients (eg, de Gelder, Pourtois, and Weiskrantz, 2002 to normal participants based on their unawareness of the relation between visual and auditory information.

Modeling the Interaction Between Semantic Agents and Semantic Web Services Using MDA Approach

NARCIS (Netherlands)

Kardas, Geylani; Göknil, Arda; Dikenelli, Oguz; Topaloglu, N. Yasemin

2007-01-01

In this paper, we present our metamodeling approach for integrating semantic web services and semantic web enabled agents under Model Driven Architecture (MDA) view which defines a conceptual framework to realize model driven development. We believe that agents must have well designed environment

ONTOLOGY BASED MEANINGFUL SEARCH USING SEMANTIC WEB AND NATURAL LANGUAGE PROCESSING TECHNIQUES

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K. Palaniammal

2013-10-01

Full Text Available The semantic web extends the current World Wide Web by adding facilities for the machine understood description of meaning. The ontology based search model is used to enhance efficiency and accuracy of information retrieval. Ontology is the core technology for the semantic web and this mechanism for representing formal and shared domain descriptions. In this paper, we proposed ontology based meaningful search using semantic web and Natural Language Processing (NLP techniques in the educational domain. First we build the educational ontology then we present the semantic search system. The search model consisting three parts which are embedding spell-check, finding synonyms using WordNet API and querying ontology using SPARQL language. The results are both sensitive to spell check and synonymous context. This paper provides more accurate results and the complete details for the selected field in a single page.

Human ecstasy (MDMA) polydrug users have altered brain activation during semantic processing.

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Watkins, Tristan J; Raj, Vidya; Lee, Junghee; Dietrich, Mary S; Cao, Aize; Blackford, Jennifer U; Salomon, Ronald M; Park, Sohee; Benningfield, Margaret M; Di Iorio, Christina R; Cowan, Ronald L

2013-05-01

Ecstasy (3,4-methylenedioxymethamphetamine [MDMA]) polydrug users have verbal memory performance that is statistically significantly lower than that of control subjects. Studies have correlated long-term MDMA use with altered brain activation in regions that play a role in verbal memory. The aim of our study was to examine the association of lifetime ecstasy use with semantic memory performance and brain activation in ecstasy polydrug users. A total of 23 abstinent ecstasy polydrug users (age = 24.57 years) and 11 controls (age = 22.36 years) performed a two-part functional magnetic resonance imaging (fMRI) semantic encoding and recognition task. To isolate brain regions activated during each semantic task, we created statistical activation maps in which brain activation was greater for word stimuli than for non-word stimuli (corrected p ecstasy polydrug users had greater activation during semantic encoding bilaterally in language processing regions, including Brodmann areas 7, 39, and 40. Of this bilateral activation, signal intensity with a peak T in the right superior parietal lobe was correlated with lifetime ecstasy use (r s = 0.43, p = 0.042). Behavioral performance did not differ between groups. These findings demonstrate that ecstasy polydrug users have increased brain activation during semantic processing. This increase in brain activation in the absence of behavioral deficits suggests that ecstasy polydrug users have reduced cortical efficiency during semantic encoding, possibly secondary to MDMA-induced 5-HT neurotoxicity. Although pre-existing differences cannot be ruled out, this suggests the possibility of a compensatory mechanism allowing ecstasy polydrug users to perform equivalently to controls, providing additional support for an association of altered cerebral neurophysiology with MDMA exposure.

Remote semantic memory is impoverished in hippocampal amnesia.

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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.

Ways of making-sense: Local gamma synchronization reveals differences between semantic processing induced by music and language.

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Barraza, Paulo; Chavez, Mario; Rodríguez, Eugenio

2016-01-01

Similar to linguistic stimuli, music can also prime the meaning of a subsequent word. However, it is so far unknown what is the brain dynamics underlying the semantic priming effect induced by music, and its relation to language. To elucidate these issues, we compare the brain oscillatory response to visual words that have been semantically primed either by a musical excerpt or by an auditory sentence. We found that semantic violation between music-word pairs triggers a classical ERP N400, and induces a sustained increase of long-distance theta phase synchrony, along with a transient increase of local gamma activity. Similar results were observed after linguistic semantic violation except for gamma activity, which increased after semantic congruence between sentence-word pairs. Our findings indicate that local gamma activity is a neural marker that signals different ways of semantic processing between music and language, revealing the dynamic and self-organized nature of the semantic processing. Copyright © 2015 Elsevier Inc. All rights reserved.

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

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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.

Re-examination of Chinese semantic processing and syntactic processing: evidence from conventional ERPs and reconstructed ERPs by residue iteration decomposition (RIDE.

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Fang Wang

Full Text Available A number of studies have explored the time course of Chinese semantic and syntactic processing. However, whether syntactic processing occurs earlier than semantics during Chinese sentence reading is still under debate. To further explore this issue, an event-related potentials (ERPs experiment was conducted on 21 native Chinese speakers who read individually-presented Chinese simple sentences (NP1+VP+NP2 word-by-word for comprehension and made semantic plausibility judgments. The transitivity of the verbs was manipulated to form three types of stimuli: congruent sentences (CON, sentences with a semantically violated NP2 following a transitive verb (semantic violation, SEM, and sentences with a semantically violated NP2 following an intransitive verb (combined semantic and syntactic violation, SEM+SYN. The ERPs evoked from the target NP2 were analyzed by using the Residue Iteration Decomposition (RIDE method to reconstruct the ERP waveform blurred by trial-to-trial variability, as well as by using the conventional ERP method based on stimulus-locked averaging. The conventional ERP analysis showed that, compared with the critical words in CON, those in SEM and SEM+SYN elicited an N400-P600 biphasic pattern. The N400 effects in both violation conditions were of similar size and distribution, but the P600 in SEM+SYN was bigger than that in SEM. Compared with the conventional ERP analysis, RIDE analysis revealed a larger N400 effect and an earlier P600 effect (in the time window of 500-800 ms instead of 570-810ms. Overall, the combination of conventional ERP analysis and the RIDE method for compensating for trial-to-trial variability confirmed the non-significant difference between SEM and SEM+SYN in the earlier N400 time window. Converging with previous findings on other Chinese structures, the current study provides further precise evidence that syntactic processing in Chinese does not occur earlier than semantic processing.

A Semantic Web management model for integrative biomedical informatics.

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Helena F Deus

2008-08-01

Full Text Available Data, data everywhere. The diversity and magnitude of the data generated in the Life Sciences defies automated articulation among complementary efforts. The additional need in this field for managing property and access permissions compounds the difficulty very significantly. This is particularly the case when the integration involves multiple domains and disciplines, even more so when it includes clinical and high throughput molecular data.The emergence of Semantic Web technologies brings the promise of meaningful interoperation between data and analysis resources. In this report we identify a core model for biomedical Knowledge Engineering applications and demonstrate how this new technology can be used to weave a management model where multiple intertwined data structures can be hosted and managed by multiple authorities in a distributed management infrastructure. Specifically, the demonstration is performed by linking data sources associated with the Lung Cancer SPORE awarded to The University of Texas MD Anderson Cancer Center at Houston and the Southwestern Medical Center at Dallas. A software prototype, available with open source at www.s3db.org, was developed and its proposed design has been made publicly available as an open source instrument for shared, distributed data management.The Semantic Web technologies have the potential to addresses the need for distributed and evolvable representations that are critical for systems Biology and translational biomedical research. As this technology is incorporated into application development we can expect that both general purpose productivity software and domain specific software installed on our personal computers will become increasingly integrated with the relevant remote resources. In this scenario, the acquisition of a new dataset should automatically trigger the delegation of its analysis.

Linked Metadata - lightweight semantics for data integration (Invited)

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Hendler, J. A.

2013-12-01

The "Linked Open Data" cloud (http://linkeddata.org) is currently used to show how the linking of datasets, supported by SPARQL endpoints, is creating a growing set of linked data assets. This linked data space has been growing rapidly, and the last version collected is estimated to have had over 35 billion 'triples.' As impressive as this may sound, there is an inherent flaw in the way the linked data story is conceived. The idea is that all of the data is represented in a linked format (generally RDF) and applications will essentially query this cloud and provide mashup capabilities between the various kinds of data that are found. The view of linking in the cloud is fairly simple -links are provided by either shared URIs or by URIs that are asserted to be owl:sameAs. This view of the linking, which primarily focuses on shared objects and subjects in RDF's subject-predicate-object representation, misses a critical aspect of Semantic Web technology. Given triples such as * A:person1 foaf:knows A:person2 * B:person3 foaf:knows B:person4 * C:person5 foaf:name 'John Doe' this view would not consider them linked (barring other assertions) even though they share a common vocabulary. In fact, we get significant clues that there are commonalities in these data items from the shared namespaces and predicates, even if the traditional 'graph' view of RDF doesn't appear to join on these. Thus, it is the linking of the data descriptions, whether as metadata or other vocabularies, that provides the linking in these cases. This observation is crucial to scientific data integration where the size of the datasets, or even the individual relationships within them, can be quite large. (Note that this is not restricted to scientific data - search engines, social networks, and massive multiuser games also create huge amounts of data.) To convert all the triples into RDF and provide individual links is often unnecessary, and is both time and space intensive. Those looking to do on the

Comparison of the neural substrates mediating the semantic processing of Korean and English words using positron emission tomography

International Nuclear Information System (INIS)

Kim, Jea Jin; Kim, Myung Sun; Cho, Sang Soo; Kwon, Jun Soo; Lee, Jae Sung; Lee, Dong Soo; Chung, June Key; Lee, Myung Chul

2001-01-01

This study was performed to search the relatively specific brain regions related to the semantic processing of Korean and English words on the one hand and the regions common to both on the other. Regional cerebral blood flow associated with different semantic tasks was examined using ( 15 O)H 2 O positron emission tomography in 13 healthy volunteers. The tasks consisted of semantic tasks for Korean words, semantic tasks for English words and control tasks using simple pictures. The regions specific and common to each language were identified by the relevant subtraction analysis using statistical parametric mapping. Common to the semantic processing of both words, the activation site was observed in the fusiform gyrus, particularly the left side. In addition, activation of the left inferior temporal gyrus was found only in the semantic processing of English words. The regions specific to Korean words were observed in multiple areas, including the right primary auditory cortex; whereas the regions specific to English words were limited to the right posterior visual area. Internal phonological process is engaged in performing the visual semantic task for Korean words of the high proficiency, whereas visual scanning plays an important role in performing the task for English words of the low proficiency

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

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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.

Semantic similarity measure in biomedical domain leverage web search engine.

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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.

Toward semantic interoperability in home health care: formally representing OASIS items for integration into a concept-oriented terminology.

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Choi, Jeungok; Jenkins, Melinda L; Cimino, James J; White, Thomas M; Bakken, Suzanne

2005-01-01

The authors aimed to (1) formally represent OASIS-B1 concepts using the Logical Observation Identifiers, Names, and Codes (LOINC) semantic structure; (2) demonstrate integration of OASIS-B1 concepts into a concept-oriented terminology, the Medical Entities Dictionary (MED); (3) examine potential hierarchical structures within LOINC among OASIS-B1 and other nursing terms; and (4) illustrate a Web-based implementation for OASIS-B1 data entry using Dialogix, a software tool with a set of functions that supports complex data entry. Two hundred nine OASIS-B1 items were dissected into the six elements of the LOINC semantic structure and then integrated into the MED hierarchy. Each OASIS-B1 term was matched to LOINC-coded nursing terms, Home Health Care Classification, the Omaha System, and the Sign and Symptom Check-List for Persons with HIV, and the extent of the match was judged based on a scale of 0 (no match) to 4 (exact match). OASIS-B1 terms were implemented as a Web-based survey using Dialogix. Of 209 terms, 204 were successfully dissected into the elements of the LOINC semantics structure and integrated into the MED with minor revisions of MED semantics. One hundred fifty-one OASIS-B1 terms were mapped to one or more of the LOINC-coded nursing terms. The LOINC semantic structure offers a standard way to add home health care data to a comprehensive patient record to facilitate data sharing for monitoring outcomes across sites and to further terminology management, decision support, and accurate information retrieval for evidence-based practice. The cross-mapping results support the possibility of a hierarchical structure of the OASIS-B1 concepts within nursing terminologies in the LOINC database.

From Science to e-Science to Semantic e-Science: A Heliosphysics Case Study

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Narock, Thomas; Fox, Peter

2011-01-01

The past few years have witnessed unparalleled efforts to make scientific data web accessible. The Semantic Web has proven invaluable in this effort; however, much of the literature is devoted to system design, ontology creation, and trials and tribulations of current technologies. In order to fully develop the nascent field of Semantic e-Science we must also evaluate systems in real-world settings. We describe a case study within the field of Heliophysics and provide a comparison of the evolutionary stages of data discovery, from manual to semantically enable. We describe the socio-technical implications of moving toward automated and intelligent data discovery. In doing so, we highlight how this process enhances what is currently being done manually in various scientific disciplines. Our case study illustrates that Semantic e-Science is more than just semantic search. The integration of search with web services, relational databases, and other cyberinfrastructure is a central tenet of our case study and one that we believe has applicability as a generalized research area within Semantic e-Science. This case study illustrates a specific example of the benefits, and limitations, of semantically replicating data discovery. We show examples of significant reductions in time and effort enable by Semantic e-Science; yet, we argue that a "complete" solution requires integrating semantic search with other research areas such as data provenance and web services.

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

Directory of Open Access Journals (Sweden)

Heng Sun

Full Text Available 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.

Science.gov (United States)

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.

Building a Semantic Framework for eScience

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Movva, S.; Ramachandran, R.; Maskey, M.; Li, X.

2009-12-01

The e-Science vision focuses on the use of advanced computing technologies to support scientists. Recent research efforts in this area have focused primarily on “enabling” use of infrastructure resources for both data and computational access especially in Geosciences. One of the existing gaps in the existing e-Science efforts has been the failure to incorporate stable semantic technologies within the design process itself. In this presentation, we describe our effort in designing a framework for e-Science built using Service Oriented Architecture. Our framework provides users capabilities to create science workflows and mine distributed data. Our e-Science framework is being designed around a mass market tool to promote reusability across many projects. Semantics is an integral part of this framework and our design goal is to leverage the latest stable semantic technologies. The use of these stable semantic technologies will provide the users of our framework the useful features such as: allow search engines to find their content with RDFa tags; create RDF triple data store for their content; create RDF end points to share with others; and semantically mash their content with other online content available as RDF end point.

Congruence from the Operator's Point of View: Compositionality Requirements on Process Semantics

Directory of Open Access Journals (Sweden)

Maciej Gazda

2010-08-01

Full Text Available One of the basic sanity properties of a behavioural semantics is that it constitutes a congruence with respect to standard process operators. This issue has been traditionally addressed by the development of rule formats for transition system specifications that define process algebras. In this paper we suggest a novel, orthogonal approach. Namely, we focus on a number of process operators, and for each of them attempt to find the widest possible class of congruences. To this end, we impose restrictions on sublanguages of Hennessy-Milner logic, so that a semantics whose modal characterization satisfies a given criterion is guaranteed to be a congruence with respect to the operator in question. We investigate action prefix, alternative composition, two restriction operators, and parallel composition.

Retrieval and Monitoring Processes during Visual Working Memory: An ERP Study of the Benefit of Visual Semantics

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Elizabeth Orme

2017-07-01

Full Text Available In this study, we examined electrophysiological indices of episodic remembering whilst participants recalled novel shapes, with and without semantic content, within a visual working memory paradigm. The components of interest were the parietal episodic (PE; 400–800 ms and late posterior negativity (LPN; 500–900 ms, as these have previously been identified as reliable markers of recollection and post-retrieval monitoring, respectively. Fifteen young adults completed a visual matrix patterns task, assessing memory for low and high semantic visual representations. Matrices with either low semantic or high semantic content (containing familiar visual forms were briefly presented to participants for study (1500 ms, followed by a retention interval (6000 ms and finally a same/different recognition phase. The event-related potentials of interest were tracked from the onset of the recognition test stimuli. Analyses revealed equivalent amplitude for the earlier PE effect for the processing of both low and high semantic stimulus types. However, the LPN was more negative-going for the processing of the low semantic stimuli. These data are discussed in terms of relatively ‘pure’ and complete retrieval of high semantic items, where support can readily be recruited from semantic memory. However, for the low semantic items additional executive resources, as indexed by the LPN, are recruited when memory monitoring and uncertainty exist in order to recall previously studied items more effectively.

Retrieval and Monitoring Processes during Visual Working Memory: An ERP Study of the Benefit of Visual Semantics.

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Orme, Elizabeth; Brown, Louise A; Riby, Leigh M

2017-01-01

In this study, we examined electrophysiological indices of episodic remembering whilst participants recalled novel shapes, with and without semantic content, within a visual working memory paradigm. The components of interest were the parietal episodic (PE; 400-800 ms) and late posterior negativity (LPN; 500-900 ms), as these have previously been identified as reliable markers of recollection and post-retrieval monitoring, respectively. Fifteen young adults completed a visual matrix patterns task, assessing memory for low and high semantic visual representations. Matrices with either low semantic or high semantic content (containing familiar visual forms) were briefly presented to participants for study (1500 ms), followed by a retention interval (6000 ms) and finally a same/different recognition phase. The event-related potentials of interest were tracked from the onset of the recognition test stimuli. Analyses revealed equivalent amplitude for the earlier PE effect for the processing of both low and high semantic stimulus types. However, the LPN was more negative-going for the processing of the low semantic stimuli. These data are discussed in terms of relatively 'pure' and complete retrieval of high semantic items, where support can readily be recruited from semantic memory. However, for the low semantic items additional executive resources, as indexed by the LPN, are recruited when memory monitoring and uncertainty exist in order to recall previously studied items more effectively.

Retrieval and Monitoring Processes during Visual Working Memory: An ERP Study of the Benefit of Visual Semantics

Science.gov (United States)

Orme, Elizabeth; Brown, Louise A.; Riby, Leigh M.

2017-01-01

In this study, we examined electrophysiological indices of episodic remembering whilst participants recalled novel shapes, with and without semantic content, within a visual working memory paradigm. The components of interest were the parietal episodic (PE; 400–800 ms) and late posterior negativity (LPN; 500–900 ms), as these have previously been identified as reliable markers of recollection and post-retrieval monitoring, respectively. Fifteen young adults completed a visual matrix patterns task, assessing memory for low and high semantic visual representations. Matrices with either low semantic or high semantic content (containing familiar visual forms) were briefly presented to participants for study (1500 ms), followed by a retention interval (6000 ms) and finally a same/different recognition phase. The event-related potentials of interest were tracked from the onset of the recognition test stimuli. Analyses revealed equivalent amplitude for the earlier PE effect for the processing of both low and high semantic stimulus types. However, the LPN was more negative-going for the processing of the low semantic stimuli. These data are discussed in terms of relatively ‘pure’ and complete retrieval of high semantic items, where support can readily be recruited from semantic memory. However, for the low semantic items additional executive resources, as indexed by the LPN, are recruited when memory monitoring and uncertainty exist in order to recall previously studied items more effectively. PMID:28725203

Auditory Distraction in Semantic Memory: A Process-Based Approach

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Marsh, John E.; Hughes, Robert W.; Jones, Dylan M.

2008-01-01

Five experiments demonstrate auditory-semantic distraction in tests of memory for semantic category-exemplars. The effects of irrelevant sound on category-exemplar recall are shown to be functionally distinct from those found in the context of serial short-term memory by showing sensitivity to: The lexical-semantic, rather than acoustic,…

A rigorous semantics for BPMN 2.0 process diagrams

CERN Document Server

Kossak, Felix; Geist, Verena; Kubovy, Jan; Natschläger, Christine; Ziebermayr, Thomas; Kopetzky, Theodorich; Freudenthaler, Bernhard; Schewe, Klaus-Dieter

2015-01-01

This book provides the most complete formal specification of the semantics of the Business Process Model and Notation 2.0 standard (BPMN) available to date, in a style that is easily understandable for a wide range of readers - not only for experts in formal methods, but e.g. also for developers of modeling tools, software architects, or graduate students specializing in business process management. BPMN - issued by the Object Management Group - is a widely used standard for business process modeling. However, major drawbacks of BPMN include its limited support for organizational modeling, i

A Ubiquitous Sensor Network Platform for Integrating Smart Devices into the Semantic Sensor Web

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de Vera, David Díaz Pardo; Izquierdo, Álvaro Sigüenza; Vercher, Jesús Bernat; Gómez, Luis Alfonso Hernández

2014-01-01

Ongoing Sensor Web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation Networks: a pilot Telco Ubiquitous Sensor Network (USN) Platform that embeds several OGC® Sensor Web services. This platform has already been deployed in large scale projects. Second, the USN-Platform is extended to explore a first approach to Semantic Sensor Web principles and technologies, so that smart devices can access Sensor Web data, allowing them also to share richer (semantically interpreted) information. An experimental scenario is presented: a smart car that consumes and produces real-world information which is integrated into the Semantic Sensor Web through a Telco USN-Platform. Performance tests revealed that observation publishing times with our experimental system were well within limits compatible with the adequate operation of smart safety assistance systems in vehicles. On the other hand, response times for complex queries on large repositories may be inappropriate for rapid reaction needs. PMID:24945678

Auditory semantic processing in dichotic listening: effects of competing speech, ear of presentation, and sentential bias on N400s to spoken words in context.

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Carey, Daniel; Mercure, Evelyne; Pizzioli, Fabrizio; Aydelott, Jennifer

2014-12-01

The effects of ear of presentation and competing speech on N400s to spoken words in context were examined in a dichotic sentence priming paradigm. Auditory sentence contexts with a strong or weak semantic bias were presented in isolation to the right or left ear, or with a competing signal presented in the other ear at a SNR of -12 dB. Target words were congruent or incongruent with the sentence meaning. Competing speech attenuated N400s to both congruent and incongruent targets, suggesting that the demand imposed by a competing signal disrupts the engagement of semantic comprehension processes. Bias strength affected N400 amplitudes differentially depending upon ear of presentation: weak contexts presented to the le/RH produced a more negative N400 response to targets than strong contexts, whereas no significant effect of bias strength was observed for sentences presented to the re/LH. The results are consistent with a model of semantic processing in which the RH relies on integrative processing strategies in the interpretation of sentence-level meaning. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Space package: Tight Integration Between Space and Semantics

NARCIS (Netherlands)

van Hage, W.R.; Wielemaker, J.; Schreiber, A.Th.

2010-01-01

Interpretation of spatial features often requires combined reasoning over geometry and semantics. We introduce the Space package, an open source SWI-Prolog extension that provides spatial indexing capabilities. Together with the existing semantic web reasoning capabilities of SWI-Prolog, this allows

Semantic memory retrieval circuit: role of pre-SMA, caudate, and thalamus.

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Hart, John; Maguire, Mandy J; Motes, Michael; Mudar, Raksha Anand; Chiang, Hsueh-Sheng; Womack, Kyle B; Kraut, Michael A

2013-07-01

We propose that pre-supplementary motor area (pre-SMA)-thalamic interactions govern processes fundamental to semantic retrieval of an integrated object memory. At the onset of semantic retrieval, pre-SMA initiates electrical interactions between multiple cortical regions associated with semantic memory subsystems encodings as indexed by an increase in theta-band EEG power. This starts between 100-150 ms after stimulus presentation and is sustained throughout the task. We posit that this activity represents initiation of the object memory search, which continues in searching for an object memory. When the correct memory is retrieved, there is a high beta-band EEG power increase, which reflects communication between pre-SMA and thalamus, designates the end of the search process and resultant in object retrieval from multiple semantic memory subsystems. This high beta signal is also detected in cortical regions. This circuit is modulated by the caudate nuclei to facilitate correct and suppress incorrect target memories. Copyright © 2012 Elsevier Inc. All rights reserved.

Retrieval from semantic memory.

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Noordman-Vonk, Wietske

1977-01-01

The present study has been concerned with the retrieval of semantic information. Retrieving semantic information is a fundamental process in almost any kind of cognitive behavior. The introduction presented the main experimental paradigms and results found in the literature on semantic memory as

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

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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

Integration of nursing assessment concepts into the medical entities dictionary using the LOINC semantic structure as a terminology model.

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Cieslowski, B J; Wajngurt, D; Cimino, J J; Bakken, S

2001-01-01

Recent investigations have tested the applicability of various terminology models for the representing nursing concepts including those related to nursing diagnoses, nursing interventions, and standardized nursing assessments as a prerequisite for building a reference terminology that supports the nursing domain. We used the semantic structure of Clinical LOINC (Logical Observations, Identifiers, Names, and Codes) as a reference terminology model to support the integration of standardized assessment terms from two nursing terminologies into the Medical Entities Dictionary (MED), the concept-oriented, metadata dictionary at New York Presbyterian Hospital. Although the LOINC semantic structure was used previously to represent laboratory terms in the MED, selected hierarchies and semantic slots required revisions in order to incorporate the nursing assessment concepts. This project was an initial step in integrating nursing assessment concepts into the MED in a manner consistent with evolving standards for reference terminology models. Moreover, the revisions provide the foundation for adding other types of standardized assessments to the MED.

The Evidence-base for Using Ontologies and Semantic Integration Methodologies to Support Integrated Chronic Disease Management in Primary and Ambulatory Care: Realist Review. Contribution of the IMIA Primary Health Care Informatics WG.

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Liyanage, H; Liaw, S-T; Kuziemsky, C; Terry, A L; Jones, S; Soler, J K; de Lusignan, S

2013-01-01

Most chronic diseases are managed in primary and ambulatory care. The chronic care model (CCM) suggests a wide range of community, technological, team and patient factors contribute to effective chronic disease management. Ontologies have the capability to enable formalised linkage of heterogeneous data sources as might be found across the elements of the CCM. To describe the evidence base for using ontologies and other semantic integration methods to support chronic disease management. We reviewed the evidence-base for the use of ontologies and other semantic integration methods within and across the elements of the CCM. We report them using a realist review describing the context in which the mechanism was applied, and any outcome measures. Most evidence was descriptive with an almost complete absence of empirical research and important gaps in the evidence-base. We found some use of ontologies and semantic integration methods for community support of the medical home and for care in the community. Ubiquitous information technology (IT) and other IT tools were deployed to support self-management support, use of shared registries, health behavioural models and knowledge discovery tools to improve delivery system design. Data quality issues restricted the use of clinical data; however there was an increased use of interoperable data and health system integration. Ontologies and semantic integration methods are emergent with limited evidence-base for their implementation. However, they have the potential to integrate the disparate community wide data sources to provide the information necessary for effective chronic disease management.

Model for Semantically Rich Point Cloud Data

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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.

MODEL FOR SEMANTICALLY RICH POINT CLOUD DATA

Directory of Open Access Journals (Sweden)

F. Poux

2017-10-01

Full Text Available 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.

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

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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.

Semantic modeling and interoperability in product and process engineering a technology for engineering informatics

CERN Document Server

2013-01-01

In the past decade, feature-based design and manufacturing has gained some momentum in various engineering domains to represent and reuse semantic patterns with effective applicability. However, the actual scope of feature application is still very limited. Semantic Modeling and Interoperability in Product and Process Engineering provides a systematic solution for the challenging engineering informatics field aiming at the enhancement of sustainable knowledge representation, implementation and reuse in an open and yet practically manageable scale.   This semantic modeling technology supports uniform, multi-facet and multi-level collaborative system engineering with heterogeneous computer-aided tools, such as CADCAM, CAE, and ERP.  This presented unified feature model can be applied to product and process representation, development, implementation and management. Practical case studies and test samples are provided to illustrate applications which can be implemented by the readers in real-world scenarios. �...

Through the eye of the PLC: semantic security monitoring for industrial processes

NARCIS (Netherlands)

Hadziosmanovic, D.; Sommer, Robin; Zambon, Emmanuele; Hartel, Pieter H.

2014-01-01

Off-the-shelf intrusion detection systems prove an ill fit for protecting industrial control systems, as they do not take their process semantics into account. Specifically, current systems fail to detect recent process control attacks that manifest as unauthorized changes to the configuration of a

Congruence from the operator's point of view: compositionality requirements on process semantics

NARCIS (Netherlands)

Gazda, M.; Fokkink, W.J.

2010-01-01

One of the basic sanity properties of a behavioural semantics is that it constitutes a congruence with respect to standard process operators. This issue has been traditionally addressed by the development of rule formats for transition system specifications that define process algebras. In this

Congruence from the operator's point of view : compositionality requirements on process semantics

NARCIS (Netherlands)

Gazda, M.W.; Fokkink, W.J.; Aceto, L.; Sobocinski, P.

2010-01-01

One of the basic sanity properties of a behavioural semantics is that it constitutes a congruence with respect to standard process operators. This issue has been traditionally addressed by the development of rule formats for transition system specifications that define process algebras. In this

Differences in Processing of Taxonomic and Sequential Relations in Semantic Memory: An fMRI Investigation

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Kuchinke, Lars; van der Meer, Elke; Krueger, Frank

2009-01-01

Conceptual knowledge of our world is represented in semantic memory in terms of concepts and semantic relations between concepts. We used functional magnetic resonance imaging (fMRI) to examine the cortical regions underlying the processing of sequential and taxonomic relations. Participants were presented verbal cues and performed three tasks:…

How semantic deficits in schizotypy help understand language and thought disorders in schizophrenia: a systematic and integrative review

Directory of Open Access Journals (Sweden)

Hélio Anderson Tonelli

2014-04-01

Full Text Available Introduction: Disorders of thought are psychopathological phenomena commonly present in schizophrenia and seem to result from deficits of semantic processing. Schizotypal personality traits consist of tendencies to think and behave that are qualitatively similar to schizophrenia, with greater vulnerability to such disorder. This study reviewed the literature about semantic processing deficits in samples of individuals with schizotypal traits and discussed the impact of current knowledge upon the comprehension of schizophrenic thought disorders. Studies about the cognitive performance of healthy individuals with schizotypal traits help understand the semantic deficits underlying psychotic thought disorders with the advantage of avoiding confounding factors usually found in samples of individuals with schizophrenia, such as the use of antipsychotics and hospitalizations. Methods: A search for articles published in Portuguese or English within the last 10 years on the databases MEDLINE, Web of Science, PsycInfo, LILACS and Biological Abstracts was conducted, using the keywords semantic processing, schizotypy and schizotypal personality disorder. Results: The search retrieved 44 manuscripts, out of which 11 were firstly chosen. Seven manuscripts were additionally included after reading these papers. Conclusion: The great majority of the included studies showed that schizotypal subjects might exhibit semantic processing deficits. They help clarify about the interfaces between cognitive, neurophysiological and neurochemical mechanisms underlying not only thought disorders, but also healthy human mind's creativity.

Semantic Priming During Sentence Processing by Young and Older Adults.

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Burke, Deborah M.; Yee, Penny L.

1984-01-01

Compares the semantic processing skills of younger adults (mean age 25) and older adults (mean age 68). After reading a sentence, subjects performed a task in which responses did not depend on retention. Results provided no evidence for age-related changes, including those associated with access to implied information. (Author/RH)

Semantic encoding and retrieval in the left inferior prefrontal cortex: a functional MRI study of task difficulty and process specificity.

Science.gov (United States)

Demb, J B; Desmond, J E; Wagner, A D; Vaidya, C J; Glover, G H; Gabrieli, J D

1995-09-01

Prefrontal cortical function was examined during semantic encoding and repetition priming using functional magnetic resonance imaging (fMRI), a noninvasive technique for localizing regional changes in blood oxygenation, a correlate of neural activity. Words studied in a semantic (deep) encoding condition were better remembered than words studied in both easier and more difficult nonsemantic (shallow) encoding conditions, with difficulty indexed by response time. The left inferior prefrontal cortex (LIPC) (Brodmann's areas 45, 46, 47) showed increased activation during semantic encoding relative to nonsemantic encoding regardless of the relative difficulty of the nonsemantic encoding task. Therefore, LIPC activation appears to be related to semantic encoding and not task difficulty. Semantic encoding decisions are performed faster the second time words are presented. This represents semantic repetition priming, a facilitation in semantic processing for previously encoded words that is not dependent on intentional recollection. The same LIPC area activated during semantic encoding showed decreased activation during repeated semantic encoding relative to initial semantic encoding of the same words. This decrease in activation during repeated encoding was process specific; it occurred when words were semantically reprocessed but not when words were nonsemantically reprocessed. The results were apparent in both individual and averaged functional maps. These findings suggest that the LIPC is part of a semantic executive system that contributes to the on-line retrieval of semantic information.

Productive extension of semantic memory in school-aged children: Relations with reading comprehension and deployment of cognitive resources.

Science.gov (United States)

Bauer, Patricia J; Blue, Shala N; Xu, Aoxiang; Esposito, Alena G

2016-07-01

We investigated 7- to 10-year-old children's productive extension of semantic memory through self-generation of new factual knowledge derived through integration of separate yet related facts learned through instruction or through reading. In Experiment 1, an experimenter read the to-be-integrated facts. Children successfully learned and integrated the information and used it to further extend their semantic knowledge, as evidenced by high levels of correct responses in open-ended and forced-choice testing. In Experiment 2, on half of the trials, the to-be-integrated facts were read by an experimenter (as in Experiment 1) and on half of the trials, children read the facts themselves. Self-generation performance was high in both conditions (experimenter- and self-read); in both conditions, self-generation of new semantic knowledge was related to an independent measure of children's reading comprehension. In Experiment 3, the way children deployed cognitive resources during reading was predictive of their subsequent recall of newly learned information derived through integration. These findings indicate self-generation of new semantic knowledge through integration in school-age children as well as relations between this productive means of extension of semantic memory and cognitive processes engaged during reading. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Ontology Design Patterns: Bridging the Gap Between Local Semantic Use Cases and Large-Scale, Long-Term Data Integration

Science.gov (United States)

Shepherd, Adam; Arko, Robert; Krisnadhi, Adila; Hitzler, Pascal; Janowicz, Krzysztof; Chandler, Cyndy; Narock, Tom; Cheatham, Michelle; Schildhauer, Mark; Jones, Matt; Raymond, Lisa; Mickle, Audrey; Finin, Tim; Fils, Doug; Carbotte, Suzanne; Lehnert, Kerstin

2015-04-01

Integrating datasets for new use cases is one of the common drivers for adopting semantic web technologies. Even though linked data principles enables this type of activity over time, the task of reconciling new ontological commitments for newer use cases can be daunting. This situation was faced by the Biological and Chemical Oceanography Data Management Office (BCO-DMO) as it sought to integrate its existing linked data with other data repositories to address newer scientific use cases as a partner in the GeoLink Project. To achieve a successful integration with other GeoLink partners, BCO-DMO's metadata would need to be described using the new ontologies developed by the GeoLink partners - a situation that could impact semantic inferencing, pre-existing software and external users of BCO-DMO's linked data. This presentation describes the process of how GeoLink is bridging the gap between local, pre-existing ontologies to achieve scientific metadata integration for all its partners through the use of ontology design patterns. GeoLink, an NSF EarthCube Building Block, brings together experts from the geosciences, computer science, and library science in an effort to improve discovery and reuse of data and knowledge. Its participating repositories include content from field expeditions, laboratory analyses, journal publications, conference presentations, theses/reports, and funding awards that span scientific studies from marine geology to marine ecology and biogeochemistry to paleoclimatology. GeoLink's outcomes include a set of reusable ontology design patterns (ODPs) that describe core geoscience concepts, a network of Linked Data published by participating repositories using those ODPs, and tools to facilitate discovery of related content in multiple repositories.

Qualitative Analysis of Integration Adapter Modeling

OpenAIRE

Ritter, Daniel; Holzleitner, Manuel

2015-01-01

Integration Adapters are a fundamental part of an integration system, since they provide (business) applications access to its messaging channel. However, their modeling and configuration remain under-represented. In previous work, the integration control and data flow syntax and semantics have been expressed in the Business Process Model and Notation (BPMN) as a semantic model for message-based integration, while adapter and the related quality of service modeling were left for further studi...

Supporting spatial data harmonization process with the use of ontologies and Semantic Web technologies

Science.gov (United States)

Strzelecki, M.; Iwaniak, A.; Łukowicz, J.; Kaczmarek, I.

2013-10-01

Nowadays, spatial information is not only used by professionals, but also by common citizens, who uses it for their daily activities. Open Data initiative states that data should be freely and unreservedly available for all users. It also applies to spatial data. As spatial data becomes widely available it is essential to publish it in form which guarantees the possibility of integrating it with other, heterogeneous data sources. Interoperability is the possibility to combine spatial data sets from different sources in a consistent way as well as providing access to it. Providing syntactic interoperability based on well-known data formats is relatively simple, unlike providing semantic interoperability, due to the multiple possible data interpretation. One of the issues connected with the problem of achieving interoperability is data harmonization. It is a process of providing access to spatial data in a representation that allows combining it with other harmonized data in a coherent way by using a common set of data product specification. Spatial data harmonization is performed by creating definition of reclassification and transformation rules (mapping schema) for source application schema. Creation of those rules is a very demanding task which requires wide domain knowledge and a detailed look into application schemas. The paper focuses on proposing methods for supporting data harmonization process, by automated or supervised creation of mapping schemas with the use of ontologies, ontology matching methods and Semantic Web technologies.

Automated Speech and Audio Analysis for Semantic Access to Multimedia

NARCIS (Netherlands)

Jong, F.M.G. de; Ordelman, R.; Huijbregts, M.

2006-01-01

The deployment and integration of audio processing tools can enhance the semantic annotation of multimedia content, and as a consequence, improve the effectiveness of conceptual access tools. This paper overviews the various ways in which automatic speech and audio analysis can contribute to

Automated speech and audio analysis for semantic access to multimedia

NARCIS (Netherlands)

de Jong, Franciska M.G.; Ordelman, Roeland J.F.; Huijbregts, M.A.H.; Avrithis, Y.; Kompatsiaris, Y.; Staab, S.; O' Connor, N.E.

2006-01-01

The deployment and integration of audio processing tools can enhance the semantic annotation of multimedia content, and as a consequence, improve the effectiveness of conceptual access tools. This paper overviews the various ways in which automatic speech and audio analysis can contribute to

Using the LOINC Semantic Structure to Integrate Community-based Survey Items into a Concept-based Enterprise Data Dictionary to Support Comparative Effectiveness Research.

Science.gov (United States)

Co, Manuel C; Boden-Albala, Bernadette; Quarles, Leigh; Wilcox, Adam; Bakken, Suzanne

2012-01-01

In designing informatics infrastructure to support comparative effectiveness research (CER), it is necessary to implement approaches for integrating heterogeneous data sources such as clinical data typically stored in clinical data warehouses and those that are normally stored in separate research databases. One strategy to support this integration is the use of a concept-oriented data dictionary with a set of semantic terminology models. The aim of this paper is to illustrate the use of the semantic structure of Clinical LOINC (Logical Observation Identifiers, Names, and Codes) in integrating community-based survey items into the Medical Entities Dictionary (MED) to support the integration of survey data with clinical data for CER studies.

Using XML technology for the ontology-based semantic integration of life science databases.

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Philippi, Stephan; Köhler, Jacob

2004-06-01

Several hundred internet accessible life science databases with constantly growing contents and varying areas of specialization are publicly available via the internet. Database integration, consequently, is a fundamental prerequisite to be able to answer complex biological questions. Due to the presence of syntactic, schematic, and semantic heterogeneities, large scale database integration at present takes considerable efforts. As there is a growing apprehension of extensible markup language (XML) as a means for data exchange in the life sciences, this article focuses on the impact of XML technology on database integration in this area. In detail, a general architecture for ontology-driven data integration based on XML technology is introduced, which overcomes some of the traditional problems in this area. As a proof of concept, a prototypical implementation of this architecture based on a native XML database and an expert system shell is described for the realization of a real world integration scenario.

Developing a semantic web model for medical differential diagnosis recommendation.

Science.gov (United States)

Mohammed, Osama; Benlamri, Rachid

2014-10-01

In this paper we describe a novel model for differential diagnosis designed to make recommendations by utilizing semantic web technologies. The model is a response to a number of requirements, ranging from incorporating essential clinical diagnostic semantics to the integration of data mining for the process of identifying candidate diseases that best explain a set of clinical features. We introduce two major components, which we find essential to the construction of an integral differential diagnosis recommendation model: the evidence-based recommender component and the proximity-based recommender component. Both approaches are driven by disease diagnosis ontologies designed specifically to enable the process of generating diagnostic recommendations. These ontologies are the disease symptom ontology and the patient ontology. The evidence-based diagnosis process develops dynamic rules based on standardized clinical pathways. The proximity-based component employs data mining to provide clinicians with diagnosis predictions, as well as generates new diagnosis rules from provided training datasets. This article describes the integration between these two components along with the developed diagnosis ontologies to form a novel medical differential diagnosis recommendation model. This article also provides test cases from the implementation of the overall model, which shows quite promising diagnostic recommendation results.

Co-speech gestures influence neural activity in brain regions associated with processing semantic information.

Science.gov (United States)

Dick, Anthony Steven; Goldin-Meadow, Susan; Hasson, Uri; Skipper, Jeremy I; Small, Steven L

2009-11-01

Everyday communication is accompanied by visual information from several sources, including co-speech gestures, which provide semantic information listeners use to help disambiguate the speaker's message. Using fMRI, we examined how gestures influence neural activity in brain regions associated with processing semantic information. The BOLD response was recorded while participants listened to stories under three audiovisual conditions and one auditory-only (speech alone) condition. In the first audiovisual condition, the storyteller produced gestures that naturally accompany speech. In the second, the storyteller made semantically unrelated hand movements. In the third, the storyteller kept her hands still. In addition to inferior parietal and posterior superior and middle temporal regions, bilateral posterior superior temporal sulcus and left anterior inferior frontal gyrus responded more strongly to speech when it was further accompanied by gesture, regardless of the semantic relation to speech. However, the right inferior frontal gyrus was sensitive to the semantic import of the hand movements, demonstrating more activity when hand movements were semantically unrelated to the accompanying speech. These findings show that perceiving hand movements during speech modulates the distributed pattern of neural activation involved in both biological motion perception and discourse comprehension, suggesting listeners attempt to find meaning, not only in the words speakers produce, but also in the hand movements that accompany speech.

The Semantic Web: From Representation to Realization

Science.gov (United States)

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.

Three Steps to Heaven: Semantic Publishing in a Real World Workflow

Directory of Open Access Journals (Sweden)

Robert Stevens

2012-11-01

Full Text Available Semantic publishing offers the promise of computable papers, enrichedvisualisation and a realisation of the linked data ideal. In reality, however, the publicationprocess contrives to prevent richer semantics while culminating in a "lumpen" PDF. In thispaper, we discuss a web-first approach to publication, and describe a three-tiered approachthat integrates with the existing authoring tooling. Critically, although it adds limitedsemantics, it does provide value to all the participants in the process: the author, the readerand the machine. 

Semantics of probabilistic processes an operational approach

CERN Document Server

Deng, Yuxin

2015-01-01

This book discusses the semantic foundations of concurrent systems with nondeterministic and probabilistic behaviour. Particular attention is given to clarifying the relationship between testing and simulation semantics and characterising bisimulations from metric, logical, and algorithmic perspectives. Besides presenting recent research outcomes in probabilistic concurrency theory, the book exemplifies the use of many mathematical techniques to solve problems in computer science, which is intended to be accessible to postgraduate students in Computer Science and Mathematics. It can also be us

Effects of relative embodiment in lexical and semantic processing of verbs.

Science.gov (United States)

Sidhu, David M; Kwan, Rachel; Pexman, Penny M; Siakaluk, Paul D

2014-06-01

Research examining semantic richness effects in visual word recognition has shown that multiple dimensions of meaning are activated in the process of word recognition (e.g., Yap et al., 2012). This research has, however, been limited to nouns. In the present research we extended the semantic richness approach to verb stimuli in order to investigate how verb meanings are represented. We characterized a dimension of relative embodiment for verbs, based on the bodily sense described by Borghi and Cimatti (2010), and collected ratings on that dimension for 687 English verbs. The relative embodiment ratings revealed that bodily experience was judged to be more important to the meanings of some verbs (e.g., dance, breathe) than to others (e.g., evaporate, expect). We then tested the effects of relative embodiment and imageability on verb processing in lexical decision (Experiment 1), action picture naming (Experiment 2), and syntactic classification (Experiment 3). In all three experiments results showed facilitatory effects of relative embodiment, but not imageability: latencies were faster for relatively more embodied verbs, even after several other lexical variables were controlled. The results suggest that relative embodiment is an important aspect of verb meaning, and that the semantic richness approach holds promise as a strategy for investigating other aspects of verb meaning. Copyright © 2014 Elsevier B.V. All rights reserved.

Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services

Science.gov (United States)

Daniel, Christel; Ouagne, David; Sadou, Eric; Forsberg, Kerstin; Gilchrist, Mark Mc; Zapletal, Eric; Paris, Nicolas; Hussain, Sajjad; Jaulent, Marie-Christine; MD, Dipka Kalra

2016-01-01

With the development of platforms enabling the use of routinely collected clinical data in the context of international clinical research, scalable solutions for cross border semantic interoperability need to be developed. Within the context of the IMI EHR4CR project, we first defined the requirements and evaluation criteria of the EHR4CR semantic interoperability platform and then developed the semantic resources and supportive services and tooling to assist hospital sites in standardizing their data for allowing the execution of the project use cases. The experience gained from the evaluation of the EHR4CR platform accessing to semantically equivalent data elements across 11 European participating EHR systems from 5 countries demonstrated how far the mediation model and mapping efforts met the expected requirements of the project. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data. PMID:27570649

Formalization of Technological Knowledge in the Field of Metallurgy using Document Classification Tools Supported with Semantic Techniques

Directory of Open Access Journals (Sweden)

Regulski K.

2017-06-01

Full Text Available The process of knowledge formalization is an essential part of decision support systems development. Creating a technological knowledge base in the field of metallurgy encountered problems in acquisition and codifying reusable computer artifacts based on text documents. The aim of the work was to adapt the algorithms for classification of documents and to develop a method of semantic integration of a created repository. Author used artificial intelligence tools: latent semantic indexing, rough sets, association rules learning and ontologies as a tool for integration. The developed methodology allowed for the creation of semantic knowledge base on the basis of documents in natural language in the field of metallurgy.

The Effect of Signal-to-Noise Ratio on Linguistic Processing in a Semantic Judgment Task: An Aging Study.

Science.gov (United States)

Stanley, Nicholas; Davis, Tara; Estis, Julie

2017-03-01

Aging effects on speech understanding in noise have primarily been assessed through speech recognition tasks. Recognition tasks, which focus on bottom-up, perceptual aspects of speech understanding, intentionally limit linguistic and cognitive factors by asking participants to only repeat what they have heard. On the other hand, linguistic processing tasks require bottom-up and top-down (linguistic, cognitive) processing skills and are, therefore, more reflective of speech understanding abilities used in everyday communication. The effect of signal-to-noise ratio (SNR) on linguistic processing ability is relatively unknown for either young (YAs) or older adults (OAs). To determine if reduced SNRs would be more deleterious to the linguistic processing of OAs than YAs, as measured by accuracy and reaction time in a semantic judgment task in competing speech. In the semantic judgment task, participants indicated via button press whether word pairs were a semantic Match or No Match. This task was performed in quiet, as well as, +3, 0, -3, and -6 dB SNR with two-talker speech competition. Seventeen YAs (20-30 yr) with normal hearing sensitivity and 17 OAs (60-68 yr) with normal hearing sensitivity or mild-to-moderate sensorineural hearing loss within age-appropriate norms. Accuracy, reaction time, and false alarm rate were measured and analyzed using a mixed design analysis of variance. A decrease in SNR level significantly reduced accuracy and increased reaction time in both YAs and OAs. However, poor SNRs affected accuracy and reaction time of Match and No Match word pairs differently. Accuracy for Match pairs declined at a steeper rate than No Match pairs in both groups as SNR decreased. In addition, reaction time for No Match pairs increased at a greater rate than Match pairs in more difficult SNRs, particularly at -3 and -6 dB SNR. False-alarm rates indicated that participants had a response bias to No Match pairs as the SNR decreased. Age-related differences were

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

Science.gov (United States)

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.

Students Thinking Process in Compiling Mathematical Proof with Semantics Strategy

Directory of Open Access Journals (Sweden)

Abdussakir Abdussakir

2015-03-01

Full Text Available Proses Berpikir Mahasiswa dalam Menyusun Bukti Matematis dengan Strategi Semantik   Abstract: This study is aimed to reveal the thinking process in proof construction performed by students with semantic strategy. This study use descriptive-qualitative approach. The thinking process of students will be analyzed using theoretical framework of David Tall about the three worlds of mathematical thinking. The result are three ways of thinking in semantic strategy, namely (1 started from formal world  then move into the symbolic or embodied-symbolic world with possibility of more than once and ends within or outside of the formal world, (2 started from symbolic world or embodied-symbolic world then move to the formal world with possibility of more than once and ends within or outside of the formal world, and (3 all thinking processes performed outside of formal world that does not obtain formal proof. Key Words: thinking process, mathematical proof, semantic strategy   Abstrak: Penelitian ini bertujuan untuk menjelaskan proses berpikir mahasiswa dalam menyusun bukti matematis dengan strategi semantik. Penelitian ini menggunakan pendekatan deskiptif-kualitatif. Analisis data dilakukan dengan menggunakan kerangka kerja David Tall tentang tiga dunia berpikir matematik. Hasil penelitian menunjukkan bahwa terdapat enam kemungkinan jalur dalam strategi semantik ditinjau dari teori tiga dunia berpikir matematis. Hasil penelitian menunjukkan ada tiga jalur berpikir mahasiswa dalam menyusun bukti matematis dengan strategi semantik, yaitu (1 bermula dari dunia berpikir formal berpindah ke dunia berpikir wujud-simbolik atau dunia berpikir simbolik dengan proses perpindahan dimungkinkan lebih dari satu kali dan berakhir di dalam atau di luar dunia berpikir formal, (2 bermula dari dunia berpikir wujud simbolik atau dunia berpikir simbolik (non RSP lalu pindah ke dunia berpikir formal dengan proses perpindahan dimungkinkan lebih dari satu kali dan berakhir di

Semantic Agent-Based Service Middleware and Simulation for Smart Cities.

Science.gov (United States)

Liu, Ming; Xu, Yang; Hu, Haixiao; Mohammed, Abdul-Wahid

2016-12-21

With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities

Directory of Open Access Journals (Sweden)

Ming Liu

2016-12-01

Full Text Available With the development of Machine-to-Machine (M2M technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C, Deployment (D, Resource (R and IOData (IO. Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities

Science.gov (United States)

Liu, Ming; Xu, Yang; Hu, Haixiao; Mohammed, Abdul-Wahid

2016-01-01

With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design. PMID:28009818

Reduced short-term memory capacity in Alzheimer's disease: the role of phonological, lexical, and semantic processing.

Science.gov (United States)

Caza, Nicole; Belleville, Sylvie

2008-05-01

Individuals with Alzheimer's disease (AD) are often reported to have reduced verbal short-term memory capacity, typically attributed to their attention/executive deficits. However, these individuals also tend to show progressive impairment of semantic, lexical, and phonological processing which may underlie their low short-term memory capacity. The goals of this study were to assess the contribution of each level of representation (phonological, lexical, and semantic) to immediate serial recall performance in 18 individuals with AD, and to examine how these linguistic effects on short-term memory were modulated by their reduced capacity to manipulate information in short-term memory associated with executive dysfunction. Results showed that individuals with AD had difficulty recalling items that relied on phonological representations, which led to increased lexicality effects relative to the control group. This finding suggests that patients have a greater reliance on lexical/semantic information than controls, possibly to make up for deficits in retention and processing of phonological material. This lexical/semantic effect was not found to be significantly correlated with patients' capacity to manipulate verbal material in short-term memory, indicating that language processing and executive deficits may independently contribute to reducing verbal short-term memory capacity in AD.

The Effect of Semantic Transparency on the Processing of Morphologically Derived Words: Evidence from Decision Latencies and Event-Related Potentials

Science.gov (United States)

Jared, Debra; Jouravlev, Olessia; Joanisse, Marc F.

2017-01-01

Decomposition theories of morphological processing in visual word recognition posit an early morpho-orthographic parser that is blind to semantic information, whereas parallel distributed processing (PDP) theories assume that the transparency of orthographic-semantic relationships influences processing from the beginning. To test these…

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

Directory of Open Access Journals (Sweden)

Gabriela D A Guardia

Full Text Available Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

Science.gov (United States)

Guardia, Gabriela D A; Pires, Luís Ferreira; Vêncio, Ricardo Z N; Malmegrim, Kelen C R; de Farias, Cléver R G

2015-01-01

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

Semantic and syntactic interoperability in online processing of big Earth observation data.

Science.gov (United States)

Sudmanns, Martin; Tiede, Dirk; Lang, Stefan; Baraldi, Andrea

2018-01-01

The challenge of enabling syntactic and semantic interoperability for comprehensive and reproducible online processing of big Earth observation (EO) data is still unsolved. Supporting both types of interoperability is one of the requirements to efficiently extract valuable information from the large amount of available multi-temporal gridded data sets. The proposed system wraps world models, (semantic interoperability) into OGC Web Processing Services (syntactic interoperability) for semantic online analyses. World models describe spatio-temporal entities and their relationships in a formal way. The proposed system serves as enabler for (1) technical interoperability using a standardised interface to be used by all types of clients and (2) allowing experts from different domains to develop complex analyses together as collaborative effort. Users are connecting the world models online to the data, which are maintained in a centralised storage as 3D spatio-temporal data cubes. It allows also non-experts to extract valuable information from EO data because data management, low-level interactions or specific software issues can be ignored. We discuss the concept of the proposed system, provide a technical implementation example and describe three use cases for extracting changes from EO images and demonstrate the usability also for non-EO, gridded, multi-temporal data sets (CORINE land cover).

Episodic and semantic memory functioning in very old age: Explanations from executive functioning and processing speed theories

Directory of Open Access Journals (Sweden)

Pauline E.J. Spaan

2015-12-01

Full Text Available Structural equation modeling was used to investigate whether age-related episodic and semantic memory impairments are better explained by decline in processing speed or executive functioning (or both, rather than directly in terms of memory components. The models tested were based on an extensive review of the literature on cognitive decline in normal aging, up to very old age. A computerized test battery, measuring episodic memory (free and cued recall; recognition, semantic memory (fluency; naming accuracy and latencies, processing speed and executive functioning, was administered to 234 elderly persons ranging from young-old to very old age (55–96 years. To avoid large variance in response times due to physical instead of cognitive limitations, no motor responses were required from participants. Age-related decline in episodic and semantic memory performance was found to be the consequence of declines in processing speed and executive functioning. Processing speed mainly mediated decline of semantic memory, whereas executive functioning mainly mediated episodic memory decline. The most parsimonious model showed that both processing speed and executive functioning attributed to memory decline but independent from one another. The results suggest that at very old age, the impact of executive dysfunctions on episodic memory performance exceeds the influence of cognitive slowing.

On the influence of typicality and age of acquisition on semantic processing: Diverging evidence from behavioural and ERP responses.

Science.gov (United States)

Räling, Romy; Holzgrefe-Lang, Julia; Schröder, Astrid; Wartenburger, Isabell

2015-08-01

Various behavioural studies show that semantic typicality (TYP) and age of acquisition (AOA) of a specific word influence processing time and accuracy during the performance of lexical-semantic tasks. This study examines the influence of TYP and AOA on semantic processing at behavioural (response times and accuracy data) and electrophysiological levels using an auditory category-member-verification task. Reaction time data reveal independent TYP and AOA effects, while in the accuracy data and the event-related potentials predominantly effects of TYP can be found. The present study thus confirms previous findings and extends evidence found in the visual modality to the auditory modality. A modality-independent influence on semantic word processing is manifested. However, with regard to the influence of AOA, the diverging results raise questions on the origin of AOA effects as well as on the interpretation of offline and online data. Hence, results will be discussed against the background of recent theories on N400 correlates in semantic processing. In addition, an argument in favour of a complementary use of research techniques will be made. Copyright © 2015 Elsevier Ltd. All rights reserved.

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction.

Science.gov (United States)

Thompson, Hannah E; Almaghyuli, Azizah; Noonan, Krist A; Barak, Ohr; Lambon Ralph, Matthew A; Jefferies, Elizabeth

2018-01-03

Semantic cognition, as described by the controlled semantic cognition (CSC) framework (Rogers et al., , Neuropsychologia, 76, 220), involves two key components: activation of coherent, generalizable concepts within a heteromodal 'hub' in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task-appropriate behaviour. Executive-semantic goal representations, largely supported by executive regions such as frontal and parietal cortex, are thought to allow the generation of non-dominant aspects of knowledge when these are appropriate for the task or context. Semantic aphasia (SA) patients have executive-semantic deficits, and these are correlated with general executive impairment. If the CSC proposal is correct, patients with executive impairment should not only exhibit impaired semantic cognition, but should also show characteristics that align with those observed in SA. This possibility remains largely untested, as patients selected on the basis that they show executive impairment (i.e., with 'dysexecutive syndrome') have not been extensively tested on tasks tapping semantic control and have not been previously compared with SA cases. We explored conceptual processing in 12 patients showing symptoms consistent with dysexecutive syndrome (DYS) and 24 SA patients, using a range of multimodal semantic assessments which manipulated control demands. Patients with executive impairments, despite not being selected to show semantic impairments, nevertheless showed parallel patterns to SA cases. They showed strong effects of distractor strength, cues and miscues, and probe-target distance, plus minimal effects of word frequency on comprehension (unlike semantic dementia patients with degradation of conceptual knowledge). This supports a component process account of semantic cognition in which retrieval is shaped by control processes, and confirms that deficits in SA patients reflect

A development framework for semantically interoperable health information systems.

Science.gov (United States)

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.

LAIR: A Language for Automated Semantics-Aware Text Sanitization based on Frame Semantics

DEFF Research Database (Denmark)

Hedegaard, Steffen; Houen, Søren; Simonsen, Jakob Grue

2009-01-01

We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires on...... with automated redaction of web pages for subjectively undesirable content; initial experiments suggest that using a small language based on semantic recognition of undesirable terms can be highly useful as a supplement to traditional methods of text sanitization.......We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires only...... limited prior programming experience. It neither contain scripting or I/O primitives, nor does it contain general loop constructions and is not Turing-complete. We have implemented a \\lair{} compiler and integrated it in a pipeline for automated redaction of web pages. We detail our experience...

The effect of combined sensory and semantic components on audio-visual speech perception in older adults

Directory of Open Access Journals (Sweden)

Corrina eMaguinness

2011-12-01

Full Text Available Previous studies have found that perception in older people benefits from multisensory over uni-sensory information. As normal speech recognition is affected by both the auditory input and the visual lip-movements of the speaker, we investigated the efficiency of audio and visual integration in an older population by manipulating the relative reliability of the auditory and visual information in speech. We also investigated the role of the semantic context of the sentence to assess whether audio-visual integration is affected by top-down semantic processing. We presented participants with audio-visual sentences in which the visual component was either blurred or not blurred. We found that there was a greater cost in recall performance for semantically meaningless speech in the audio-visual blur compared to audio-visual no blur condition and this effect was specific to the older group. Our findings have implications for understanding how aging affects efficient multisensory integration for the perception of speech and suggests that multisensory inputs may benefit speech perception in older adults when the semantic content of the speech is unpredictable.

A Semantic Grid Oriented to E-Tourism

Science.gov (United States)

Zhang, Xiao Ming

With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.

Phonological and semantic processing during comprehension in Wernicke's aphasia: An N400 and Phonological Mapping Negativity Study.

Science.gov (United States)

Robson, Holly; Pilkington, Emma; Evans, Louise; DeLuca, Vincent; Keidel, James L

2017-06-01

Comprehension impairments in Wernicke's aphasia are thought to result from a combination of impaired phonological and semantic processes. However, the relationship between these cognitive processes and language comprehension has only been inferred through offline neuropsychological tasks. This study used ERPs to investigate phonological and semantic processing during online single word comprehension. EEG was recorded in a group of Wernicke's aphasia n=8 and control participants n=10 while performing a word-picture verification task. The N400 and Phonological Mapping Negativity/Phonological Mismatch Negativity (PMN) event-related potential components were investigated as an index of semantic and phonological processing, respectively. Individuals with Wernicke's aphasia displayed reduced and inconsistent N400 and PMN effects in comparison to control participants. Reduced N400 effects in the WA group were simulated in the control group by artificially degrading speech perception. Correlation analyses in the Wernicke's aphasia group found that PMN but not N400 amplitude was associated with behavioural word-picture verification performance. The results confirm impairments at both phonological and semantic stages of comprehension in Wernicke's aphasia. However, reduced N400 responses in Wernicke's aphasia are at least partially attributable to earlier phonological processing impairments. The results provide further support for the traditional model of Wernicke's aphasia which claims a causative link between phonological processing and language comprehension impairments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Grammatical markers switch roles and elicit different electrophysiological responses under shallow and deep semantic requirements.

Science.gov (United States)

Soshi, Takahiro; Nakajima, Heizo; Hagiwara, Hiroko

2016-10-01

Static knowledge about the grammar of a natural language is represented in the cortico-subcortical system. However, the differences in dynamic verbal processing under different cognitive conditions are unclear. To clarify this, we conducted an electrophysiological experiment involving a semantic priming paradigm in which semantically congruent or incongruent word sequences (prime nouns-target verbs) were randomly presented. We examined the event-related brain potentials that occurred in response to congruent and incongruent target words that were preceded by primes with or without grammatical case markers. The two participant groups performed either the shallow (lexical judgment) or deep (direct semantic judgment) semantic tasks. We hypothesized that, irrespective of the case markers, the congruent targets would reduce centro-posterior N400 activities under the deep semantic condition, which induces selective attention to the semantic relatedness of content words. However, the same congruent targets with correct case markers would reduce lateralized negativity under the shallow semantic condition because grammatical case markers are related to automatic structural integration under semantically unattended conditions. We observed that congruent targets (e.g., 'open') that were preceded by primes with congruent case markers (e.g., 'shutter-object case') reduced lateralized negativity under the shallow semantic condition. In contrast, congruent targets, irrespective of case markers, consistently yielded N400 reductions under the deep semantic condition. To summarize, human neural verbal processing differed in response to the same grammatical markers in the same verbal expressions under semantically attended or unattended conditions.

Emotion processing in the aging brain is modulated by semantic elaboration

OpenAIRE

Ritchey, Maureen; Bessette-Symons, Brandy; Hayes, Scott M.; Cabeza, Roberto

2010-01-01

The neural correlates of emotion processing have been shown to vary with age: older adults (OAs) exhibit increased frontal activations and, under some circumstances, decreased amygdala activations relative to young adults (YAs) during emotion processing. Some of these differences are additionally modulated by valence, with age-related biases toward positive versus negative stimuli, and are thought to depend on OAs’ capacity for controlled elaboration. However, the role of semantic elaboration...

The role of emotion and attention in semantic processing: Evidence from N400

NARCIS (Netherlands)

Chwilla, D.J.; Tromp, J.

2013-01-01

Does emotional state affect language processing? Little yet is known about the interface between language and emotion. With regard to semantic processing we have shown that emotional state modulates the standard N400 effect. In particular, the N400 cloze probability effect was strongly reduced in a

A Concept Lattice for Semantic Integration of Geo-Ontologies Based on Weight of Inclusion Degree Importance and Information Entropy

Directory of Open Access Journals (Sweden)

Jia Xiao

2016-11-01

Full Text Available Constructing a merged concept lattice with formal concept analysis (FCA is an important research direction in the field of integrating multi-source geo-ontologies. Extracting essential geographical properties and reducing the concept lattice are two key points of previous research. A formal integration method is proposed to address the challenges in these two areas. We first extract essential properties from multi-source geo-ontologies and use FCA to build a merged formal context. Second, the combined importance weight of each single attribute of the formal context is calculated by introducing the inclusion degree importance from rough set theory and information entropy; then a weighted formal context is built from the merged formal context. Third, a combined weighted concept lattice is established from the weighted formal context with FCA and the importance weight value of every concept is defined as the sum of weight of attributes belonging to the concept’s intent. Finally, semantic granularity of concept is defined by its importance weight; we, then gradually reduce the weighted concept lattice by setting up diminishing threshold of semantic granularity. Additionally, all of those reduced lattices are organized into a regular hierarchy structure based on the threshold of semantic granularity. A workflow is designed to demonstrate this procedure. A case study is conducted to show feasibility and validity of this method and the procedure to integrate multi-source geo-ontologies.

Delineating the effect of semantic congruency on episodic memory: the role of integration and relatedness.

Science.gov (United States)

Bein, Oded; Livneh, Neta; Reggev, Niv; Gilead, Michael; Goshen-Gottstein, Yonatan; Maril, Anat

2015-01-01

A fundamental challenge in the study of learning and memory is to understand the role of existing knowledge in the encoding and retrieval of new episodic information. The importance of prior knowledge in memory is demonstrated in the congruency effect-the robust finding wherein participants display better memory for items that are compatible, rather than incompatible, with their pre-existing semantic knowledge. Despite its robustness, the mechanism underlying this effect is not well understood. In four studies, we provide evidence that demonstrates the privileged explanatory power of the elaboration-integration account over alternative hypotheses. Furthermore, we question the implicit assumption that the congruency effect pertains to the truthfulness/sensibility of a subject-predicate proposition, and show that congruency is a function of semantic relatedness between item and context words.

Delineating the effect of semantic congruency on episodic memory: the role of integration and relatedness.

Directory of Open Access Journals (Sweden)

Oded Bein

Full Text Available A fundamental challenge in the study of learning and memory is to understand the role of existing knowledge in the encoding and retrieval of new episodic information. The importance of prior knowledge in memory is demonstrated in the congruency effect-the robust finding wherein participants display better memory for items that are compatible, rather than incompatible, with their pre-existing semantic knowledge. Despite its robustness, the mechanism underlying this effect is not well understood. In four studies, we provide evidence that demonstrates the privileged explanatory power of the elaboration-integration account over alternative hypotheses. Furthermore, we question the implicit assumption that the congruency effect pertains to the truthfulness/sensibility of a subject-predicate proposition, and show that congruency is a function of semantic relatedness between item and context words.

Recruitment of Anterior and Posterior Structures in Lexical-Semantic Processing: An fMRI Study Comparing Implicit and Explicit Tasks

Science.gov (United States)

Ruff, Ilana; Blumstein, Sheila E.; Myers, Emily B.; Hutchison, Emmette

2008-01-01

Previous studies examining explicit semantic processing have consistently shown activation of the left inferior frontal gyrus (IFG). In contrast, implicit semantic processing tasks have shown activation in posterior areas including the superior temporal gyrus (STG) and the middle temporal gyrus (MTG) with less consistent activation in the IFG.…

Frontal lobe damage impairs process and content in semantic memory: evidence from category-specific effects in progressive non-fluent aphasia.

Science.gov (United States)

Reilly, Jamie; Rodriguez, Amy D; Peelle, Jonathan E; Grossman, Murray

2011-06-01

Portions of left inferior frontal cortex have been linked to semantic memory both in terms of the content of conceptual representation (e.g., motor aspects in an embodied semantics framework) and the cognitive processes used to access these representations (e.g., response selection). Progressive non-fluent aphasia (PNFA) is a neurodegenerative condition characterized by progressive atrophy of left inferior frontal cortex. PNFA can, therefore, provide a lesion model for examining the impact of frontal lobe damage on semantic processing and content. In the current study we examined picture naming in a cohort of PNFA patients across a variety of semantic categories. An embodied approach to semantic memory holds that sensorimotor features such as self-initiated action may assume differential importance for the representation of manufactured artifacts (e.g., naming hand tools). Embodiment theories might therefore predict that patients with frontal damage would be differentially impaired on manufactured artifacts relative to natural kinds, and this prediction was borne out. We also examined patterns of naming errors across a wide range of semantic categories and found that naming error distributions were heterogeneous. Although PNFA patients performed worse overall on naming manufactured artifacts, there was no reliable relationship between anomia and manipulability across semantic categories. These results add to a growing body of research arguing against a purely sensorimotor account of semantic memory, suggesting instead a more nuanced balance of process and content in how the brain represents conceptual knowledge. Copyright © 2010 Elsevier Srl. All rights reserved.

Historical Process and Semantic Study of Rhetorical Apostrophe

Directory of Open Access Journals (Sweden)

Abdollah Radmard

2013-05-01

, foregrounding: apostrophe destroys the familiar and common processes of words and sentences and hence creates pleasure and surprises the reader . Thus, words become foregrounded and more pleasant and tasteful .   2. Art ambiguity : apostrophe creates the sense of defamiliarization a nd unexpected changes and makes the text ambiguous. it makes the reader to explore and understand the ambiguity and the result would be the reader's enjoyment .   3. Increasing text coherence : apostrophe in its broad sense is based on the collocation axis. Semantic cohesion and coherence can be achieved by the collocation of couplets and hemistiches. Although using apostrophe destroys the form and body of the language, it makes more motivation and tension in text and strengthens the vertical axis of the language and finally increases the coherence.

Electrophysiology of prosodic and lexical-semantic processing during sentence comprehension in aphasia.

Science.gov (United States)

Sheppard, Shannon M; Love, Tracy; Midgley, Katherine J; Holcomb, Phillip J; Shapiro, Lewis P

2017-12-01

Event-related potentials (ERPs) were used to examine how individuals with aphasia and a group of age-matched controls use prosody and themattic fit information in sentences containing temporary syntactic ambiguities. Two groups of individuals with aphasia were investigated; those demonstrating relatively good sentence comprehension whose primary language difficulty is anomia (Individuals with Anomic Aphasia (IWAA)), and those who demonstrate impaired sentence comprehension whose primary diagnosis is Broca's aphasia (Individuals with Broca's Aphasia (IWBA)). The stimuli had early closure syntactic structure and contained a temporary early closure (correct)/late closure (incorrect) syntactic ambiguity. The prosody was manipulated to either be congruent or incongruent, and the temporarily ambiguous NP was also manipulated to either be a plausible or an implausible continuation for the subordinate verb (e.g., "While the band played the song/the beer pleased all the customers."). It was hypothesized that an implausible NP in sentences with incongruent prosody may provide the parser with a plausibility cue that could be used to predict syntactic structure. The results revealed that incongruent prosody paired with a plausibility cue resulted in an N400-P600 complex at the implausible NP (the beer) in both the controls and the IWAAs, yet incongruent prosody without a plausibility cue resulted in an N400-P600 at the critical verb (pleased) only in healthy controls. IWBAs did not show evidence of N400 or P600 effects at the ambiguous NP or critical verb, although they did show evidence of a delayed N400 effect at the sentence-final word in sentences with incongruent prosody. These results suggest that IWAAs have difficulty integrating prosodic cues with underlying syntactic structure when lexical-semantic information is not available to aid their parse. IWBAs have difficulty integrating both prosodic and lexical-semantic cues with syntactic structure, likely due to a

Morphological Cues for Lexical Semantics

National Research Council Canada - National Science Library

Light, Marc

1996-01-01

Most natural language processing tasks require lexical semantic information such as verbal argument structure and selectional restrictions, corresponding nominal semantic class, verbal aspectual class...

Semantic Search of Web Services

Science.gov (United States)

Hao, Ke

2013-01-01

This dissertation addresses semantic search of Web services using natural language processing. We first survey various existing approaches, focusing on the fact that the expensive costs of current semantic annotation frameworks result in limited use of semantic search for large scale applications. We then propose a vector space model based service…

Higher Language Ability is Related to Angular Gyrus Activation Increase During Semantic Processing, Independent of Sentence Incongruency

Science.gov (United States)

Van Ettinger-Veenstra, Helene; McAllister, Anita; Lundberg, Peter; Karlsson, Thomas; Engström, Maria

2016-01-01

This study investigates the relation between individual language ability and neural semantic processing abilities. Our aim was to explore whether high-level language ability would correlate to decreased activation in language-specific regions or rather increased activation in supporting language regions during processing of sentences. Moreover, we were interested if observed neural activation patterns are modulated by semantic incongruency similarly to previously observed changes upon syntactic congruency modulation. We investigated 27 healthy adults with a sentence reading task—which tapped language comprehension and inference, and modulated sentence congruency—employing functional magnetic resonance imaging (fMRI). We assessed the relation between neural activation, congruency modulation, and test performance on a high-level language ability assessment with multiple regression analysis. Our results showed increased activation in the left-hemispheric angular gyrus extending to the temporal lobe related to high language ability. This effect was independent of semantic congruency, and no significant relation between language ability and incongruency modulation was observed. Furthermore, there was a significant increase of activation in the inferior frontal gyrus (IFG) bilaterally when the sentences were incongruent, indicating that processing incongruent sentences was more demanding than processing congruent sentences and required increased activation in language regions. The correlation of high-level language ability with increased rather than decreased activation in the left angular gyrus, a region specific for language processing, is opposed to what the neural efficiency hypothesis would predict. We can conclude that no evidence is found for an interaction between semantic congruency related brain activation and high-level language performance, even though the semantic incongruent condition shows to be more demanding and evoking more neural activation. PMID

Higher language ability is related to angular gyrus activation increase during semantic processing, independent of sentence incongruency

Directory of Open Access Journals (Sweden)

Helene eVan Ettinger-Veenstra

2016-03-01

Full Text Available This study investigates the relation between individual language ability and neural semantic processing abilities. Our aim was to explore whether high-level language ability would correlate to decreased activation in language-specific regions or rather increased activation in supporting language regions during processing of sentences. Moreover, we were interested if observed neural activation patterns are modulated by semantic incongruency similarly to previously observed changes upon syntactic congruency modulation. We investigated 27 healthy adults with a sentence reading task - which tapped language comprehension and inference, and modulated sentence congruency - employing functional magnetic resonance imaging. We assessed the relation between neural activation, congruency modulation, and test performance on a high-level language ability assessment with multiple regression analysis. Our results showed increased activation in the left-hemispheric angular gyrus extending to the temporal lobe related to high language ability. This effect was independent of semantic congruency, and no significant relation between language ability and incongruency modulation was observed. Furthermore, a significant increase of activation in the inferior frontal gyrus bilaterally when the sentences were incongruent, indicating that processing incongruent sentences was more demanding than processing congruent sentences and required increased activation in language regions. The correlation of high-level language ability with increased rather than decreased activation in the left angular gyrus, a region specific for language processing is opposed to what the neural efficiency hypothesis would predict. We can conclude that there is no evidence found for an interaction between semantic congruency related brain activation and high-level language performance, even though the semantic incongruent condition shows to be more demanding and evoking more neural activation.

Reactive Kripke semantics

CERN Document Server

Gabbay, Dov M

2013-01-01

This text offers an extension to the traditional Kripke semantics for non-classical logics by adding the notion of reactivity. Reactive Kripke models change their accessibility relation as we progress in the evaluation process of formulas in the model. This feature makes the reactive Kripke semantics strictly stronger and more applicable than the traditional one. Here we investigate the properties and axiomatisations of this new and most effective semantics, and we offer a wide landscape of applications of the idea of reactivity. Applied topics include reactive automata, reactive grammars, rea

Scandinavian Semantics and the Human Body

DEFF Research Database (Denmark)

Levisen, Carsten

2015-01-01

, it is demonstrated that Scandinavian and English systems differ significantly in some aspects of the way in which the construe the human body with words. The study ventures an innovative combination of methods, pairing the Natural Semantic Metalanguage (NSM) approach to linguistic and conceptual analysis......This paper presents an ethnolinguistic analysis of how the space between the head and the body is construed in Scandinavian semantic systems vis-a-vis the semantic system of English. With an extensive case study of neck-related meanings in Danish, and with cross-Scandinavian reference...... with empirical evidence from the Evolution of Semantic Systems (EoSS) project. This combination of empirical and interpretative tools helps to integrate evidence from semantics and semiotics, pinning out in great detail the intricacies of the meanings of particular body words. The paper concludes that body words...

An Integrated Software Framework to Support Semantic Modeling and Reasoning of Spatiotemporal Change of Geographical Objects: A Use Case of Land Use and Land Cover Change Study

Directory of Open Access Journals (Sweden)

Wenwen Li

2016-09-01

Full Text Available Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in effective organization, representation and modeling of such information. This study proposes and implements an integrated computational framework to support the modeling, semantic and spatial reasoning of change information with regard to space, time and topology. We first proposed a conceptual model to formally represent the spatiotemporal variation of change data, which is essential knowledge to support various environmental and social studies, such as deforestation and urbanization studies. Then, a spatial ontology was created to encode these semantic spatiotemporal data in a machine-understandable format. Based on the knowledge defined in the ontology and related reasoning rules, a semantic platform was developed to support the semantic query and change trajectory reasoning of areas with LULCC. This semantic platform is innovative, as it integrates semantic and spatial reasoning into a coherent computational and operational software framework to support automated semantic analysis of time series data that can go beyond LULC datasets. In addition, this system scales well as the amount of data increases, validated by a number of experimental results. This work contributes significantly to both the geospatial Semantic Web and GIScience communities in terms of the establishment of the (web-based semantic platform for collaborative question answering and decision-making.

Natural Language Processing (NLP), Machine Learning (ML), and Semantics in Polar Science

Science.gov (United States)

Duerr, R.; Ramdeen, S.

2017-12-01

One of the interesting features of Polar Science is that it historically has been extremely interdisciplinary, encompassing all of the physical and social sciences. Given the ubiquity of specialized terminology in each field, enabling researchers to find, understand, and use all of the heterogeneous data needed for polar research continues to be a bottleneck. Within the informatics community, semantics has broadly accepted as a solution to these problems, yet progress in developing reusable semantic resources has been slow. The NSF-funded ClearEarth project has been adapting the methods and tools from other communities such as Biomedicine to the Earth sciences with the goal of enhancing progress and the rate at which the needed semantic resources can be created. One of the outcomes of the project has been a better understanding of the differences in the way linguists and physical scientists understand disciplinary text. One example of these differences is the tendency for each discipline and often disciplinary subfields to expend effort in creating discipline specific glossaries where individual terms often are comprised of more than one word (e.g., first-year sea ice). Often each term in a glossary is imbued with substantial contextual or physical meaning - meanings which are rarely explicitly called out within disciplinary texts; meaning which are therefore not immediately accessible to those outside that discipline or subfield; meanings which can often be represented semantically. Here we show how recognition of these difference and the use of glossaries can be used to speed up the annotation processes endemic to NLP, enable inter-community recognition and possible reconciliation of terminology differences. A number of processes and tools will be described, as will progress towards semi-automated generation of ontology structures.

NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease.

Science.gov (United States)

Iyappan, Anandhi; Kawalia, Shweta Bagewadi; Raschka, Tamara; Hofmann-Apitius, Martin; Senger, Philipp

2016-07-08

Neurodegenerative diseases are incurable and debilitating indications with huge social and economic impact, where much is still to be learnt about the underlying molecular events. Mechanistic disease models could offer a knowledge framework to help decipher the complex interactions that occur at molecular and cellular levels. This motivates the need for the development of an approach integrating highly curated and heterogeneous data into a disease model of different regulatory data layers. Although several disease models exist, they often do not consider the quality of underlying data. Moreover, even with the current advancements in semantic web technology, we still do not have cure for complex diseases like Alzheimer's disease. One of the key reasons accountable for this could be the increasing gap between generated data and the derived knowledge. In this paper, we describe an approach, called as NeuroRDF, to develop an integrative framework for modeling curated knowledge in the area of complex neurodegenerative diseases. The core of this strategy lies in the usage of well curated and context specific data for integration into one single semantic web-based framework, RDF. This increases the probability of the derived knowledge to be novel and reliable in a specific disease context. This infrastructure integrates highly curated data from databases (Bind, IntAct, etc.), literature (PubMed), and gene expression resources (such as GEO and ArrayExpress). We illustrate the effectiveness of our approach by asking real-world biomedical questions that link these resources to prioritize the plausible biomarker candidates. Among the 13 prioritized candidate genes, we identified MIF to be a potential emerging candidate due to its role as a pro-inflammatory cytokine. We additionally report on the effort and challenges faced during generation of such an indication-specific knowledge base comprising of curated and quality-controlled data. Although many alternative approaches

Disturbance of semantic processing in temporal lobe epilepsy demonstrated with scalp ERPs.

Science.gov (United States)

Miyamoto, T; Katayama, J I; Kohsaka, M; Koyama, T

2000-12-01

We investigated event-related potentials (N400, LPC and CNV) elicited in temporal lobe epilepsy (TLE) patients and control subjects from scalp electrodes, using a word-pair category matching paradigm. Each prime consisted of a Japanese noun (constructed from 2-4 characters of the Hiragana) followed by a Chinese character (Kanji) as the target, the latter representing one of five semantic categories. There were two equally probable target conditions: match or mismatch. Each target was preceded by a prime, either belonging to, or not belonging to, the same semantic category. The subjects were required to respond with a specified button press to the given target, according to the condition. We found RTs to be longer under the mismatch condition in both subject groups. The N400 amplitude was reduced in TLE subjects under both conditions, although LPC and CNV amplitudes showed no significant differences. These results suggest that scalp N400 is capable of demonstrating disturbance of semantic processing in TLE non-invasively. Copyright 2000 BEA Trading Ltd.

From Sensory Perception to Lexical-Semantic Processing: An ERP Study in Non-Verbal Children with Autism.

Science.gov (United States)

Cantiani, Chiara; Choudhury, Naseem A; Yu, Yan H; Shafer, Valerie L; Schwartz, Richard G; Benasich, April A

2016-01-01

This study examines electrocortical activity associated with visual and auditory sensory perception and lexical-semantic processing in nonverbal (NV) or minimally-verbal (MV) children with Autism Spectrum Disorder (ASD). Currently, there is no agreement on whether these children comprehend incoming linguistic information and whether their perception is comparable to that of typically developing children. Event-related potentials (ERPs) of 10 NV/MV children with ASD and 10 neurotypical children were recorded during a picture-word matching paradigm. Atypical ERP responses were evident at all levels of processing in children with ASD. Basic perceptual processing was delayed in both visual and auditory domains but overall was similar in amplitude to typically-developing children. However, significant differences between groups were found at the lexical-semantic level, suggesting more atypical higher-order processes. The results suggest that although basic perception is relatively preserved in NV/MV children with ASD, higher levels of processing, including lexical- semantic functions, are impaired. The use of passive ERP paradigms that do not require active participant response shows significant potential for assessment of non-compliant populations such as NV/MV children with ASD.

From Sensory Perception to Lexical-Semantic Processing: An ERP Study in Non-Verbal Children with Autism

Science.gov (United States)

Cantiani, Chiara; Choudhury, Naseem A.; Yu, Yan H.; Shafer, Valerie L.; Schwartz, Richard G.; Benasich, April A.

2016-01-01

This study examines electrocortical activity associated with visual and auditory sensory perception and lexical-semantic processing in nonverbal (NV) or minimally-verbal (MV) children with Autism Spectrum Disorder (ASD). Currently, there is no agreement on whether these children comprehend incoming linguistic information and whether their perception is comparable to that of typically developing children. Event-related potentials (ERPs) of 10 NV/MV children with ASD and 10 neurotypical children were recorded during a picture-word matching paradigm. Atypical ERP responses were evident at all levels of processing in children with ASD. Basic perceptual processing was delayed in both visual and auditory domains but overall was similar in amplitude to typically-developing children. However, significant differences between groups were found at the lexical-semantic level, suggesting more atypical higher-order processes. The results suggest that although basic perception is relatively preserved in NV/MV children with ASD, higher levels of processing, including lexical- semantic functions, are impaired. The use of passive ERP paradigms that do not require active participant response shows significant potential for assessment of non-compliant populations such as NV/MV children with ASD. PMID:27560378

A Framework for Semantic Recovery Strategies in Case of Process Activity Failures.

NARCIS (Netherlands)

Rinderle, S.B.; Bassil, S.; Reichert, M.U.; Manolopoulos, Y.; Filipe, J.; Constantopoulos, P.; Cordeiro, J.

During automated process execution semantic activity failures may frequently occur, e.g., when a vehicle transporting a container has a breakdown. So far there are no applicable solutions to overcome such exceptional situations. Often the only possibility is to cancel and roll back respective

Rational integration of noisy evidence and prior semantic expectations in sentence interpretation.

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Gibson, Edward; Bergen, Leon; Piantadosi, Steven T

2013-05-14

Sentence processing theories typically assume that the input to our language processing mechanisms is an error-free sequence of words. However, this assumption is an oversimplification because noise is present in typical language use (for instance, due to a noisy environment, producer errors, or perceiver errors). A complete theory of human sentence comprehension therefore needs to explain how humans understand language given imperfect input. Indeed, like many cognitive systems, language processing mechanisms may even be "well designed"--in this case for the task of recovering intended meaning from noisy utterances. In particular, comprehension mechanisms may be sensitive to the types of information that an idealized statistical comprehender would be sensitive to. Here, we evaluate four predictions about such a rational (Bayesian) noisy-channel language comprehender in a sentence comprehension task: (i) semantic cues should pull sentence interpretation towards plausible meanings, especially if the wording of the more plausible meaning is close to the observed utterance in terms of the number of edits; (ii) this process should asymmetrically treat insertions and deletions due to the Bayesian "size principle"; such nonliteral interpretation of sentences should (iii) increase with the perceived noise rate of the communicative situation and (iv) decrease if semantically anomalous meanings are more likely to be communicated. These predictions are borne out, strongly suggesting that human language relies on rational statistical inference over a noisy channel.

Grammatical markers switch roles and elicit different electrophysiological responses under shallow and deep semantic requirements

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Takahiro Soshi

2016-10-01

Full Text Available Static knowledge about the grammar of a natural language is represented in the cortico-subcortical system. However, the differences in dynamic verbal processing under different cognitive conditions are unclear. To clarify this, we conducted an electrophysiological experiment involving a semantic priming paradigm in which semantically congruent or incongruent word sequences (prime nouns–target verbs were randomly presented. We examined the event-related brain potentials that occurred in response to congruent and incongruent target words that were preceded by primes with or without grammatical case markers. The two participant groups performed either the shallow (lexical judgment or deep (direct semantic judgment semantic tasks. We hypothesized that, irrespective of the case markers, the congruent targets would reduce centro-posterior N400 activities under the deep semantic condition, which induces selective attention to the semantic relatedness of content words. However, the same congruent targets with correct case markers would reduce lateralized negativity under the shallow semantic condition because grammatical case markers are related to automatic structural integration under semantically unattended conditions. We observed that congruent targets (e.g., ‘open' that were preceded by primes with congruent case markers (e.g., ‘shutter-object case' reduced lateralized negativity under the shallow semantic condition. In contrast, congruent targets, irrespective of case markers, consistently yielded N400 reductions under the deep semantic condition. To summarize, human neural verbal processing differed in response to the same grammatical markers in the same verbal expressions under semantically attended or unattended conditions. Keyword: Neuroscience

Implicit and explicit processing in deep dyslexia: Semantic blocking as a test for failure of inhibition in the phonological output lexicon.

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Colangelo, Annette; Buchanan, Lori

2006-12-01

The failure of inhibition hypothesis posits a theoretical distinction between implicit and explicit access in deep dyslexia. Specifically, the effects of failure of inhibition are assumed only in conditions that have an explicit selection requirement in the context of production (i.e., aloud reading). In contrast, the failure of inhibition hypothesis proposes that implicit processing and explicit access to semantic information without production demands are intact in deep dyslexia. Evidence for intact implicit and explicit access requires that performance in deep dyslexia parallels that observed in neurologically intact participants on tasks based on implicit and explicit processes. In other words, deep dyslexics should produce normal effects in conditions with implicit task demands (i.e., lexical decision) and on tasks based on explicit access without production (i.e., forced choice semantic decisions) because failure of inhibition does not impact the availability of lexical information, only explicit retrieval in the context of production. This research examined the distinction between implicit and explicit processes in deep dyslexia using semantic blocking in lexical decision and forced choice semantic decisions as a test for the failure of inhibition hypothesis. The results of the semantic blocking paradigm support the distinction between implicit and explicit processing and provide evidence for failure of inhibition as an explanation for semantic errors in deep dyslexia.

Semantic Memory in the Clinical Progression of Alzheimer Disease.

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Tchakoute, Christophe T; Sainani, Kristin L; Henderson, Victor W

2017-09-01

Semantic memory measures may be useful in tracking and predicting progression of Alzheimer disease. We investigated relationships among semantic memory tasks and their 1-year predictive value in women with Alzheimer disease. We conducted secondary analyses of a randomized clinical trial of raloxifene in 42 women with late-onset mild-to-moderate Alzheimer disease. We assessed semantic memory with tests of oral confrontation naming, category fluency, semantic recognition and semantic naming, and semantic density in written narrative discourse. We measured global cognition (Alzheimer Disease Assessment Scale, cognitive subscale), dementia severity (Clinical Dementia Rating sum of boxes), and daily function (Activities of Daily Living Inventory) at baseline and 1 year. At baseline and 1 year, most semantic memory scores correlated highly or moderately with each other and with global cognition, dementia severity, and daily function. Semantic memory task performance at 1 year had worsened one-third to one-half standard deviation. Factor analysis of baseline test scores distinguished processes in semantic and lexical retrieval (semantic recognition, semantic naming, confrontation naming) from processes in lexical search (semantic density, category fluency). The semantic-lexical retrieval factor predicted global cognition at 1 year. Considered separately, baseline confrontation naming and category fluency predicted dementia severity, while semantic recognition and a composite of semantic recognition and semantic naming predicted global cognition. No individual semantic memory test predicted daily function. Semantic-lexical retrieval and lexical search may represent distinct aspects of semantic memory. Semantic memory processes are sensitive to cognitive decline and dementia severity in Alzheimer disease.

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

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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

Towards a neural basis of processing musical semantics

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Koelsch, Stefan

2011-06-01

Processing of meaning is critical for language perception, and therefore the majority of research on meaning processing has focused on the semantic, lexical, conceptual, and propositional processing of language. However, music is another a means of communication, and meaning also emerges from the interpretation of musical information. This article provides a framework for the investigation of the processing of musical meaning, and reviews neuroscience studies investigating this issue. These studies reveal two neural correlates of meaning processing, the N400 and the N5 (which are both components of the event-related electric brain potential). Here I argue that the N400 can be elicited by musical stimuli due to the processing of extra-musical meaning, whereas the N5 can be elicited due to the processing of intra-musical meaning. Notably, whereas the N400 can be elicited by both linguistic and musical stimuli, the N5 has so far only been observed for the processing of meaning in music. Thus, knowledge about both the N400 and the N5 can advance our understanding of how the human brain processes meaning information.

Considering the role of semantic memory in episodic future thinking: evidence from semantic dementia.

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Irish, Muireann; Addis, Donna Rose; Hodges, John R; Piguet, Olivier

2012-07-01

analyses that confirmed the relation between semantic memory deficits and episodic future thinking in semantic dementia, in contrast with the role of episodic memory deficits and episodic future thinking in Alzheimer's disease. Our findings demonstrate that semantic knowledge is critical for the construction of novel future events, providing the necessary scaffolding into which episodic details can be integrated. Further research is necessary to elucidate the precise contribution of semantic memory to future thinking, and to explore how deficits in self-projection manifest on behavioural and social levels in different dementia subtypes.

High Performance Descriptive Semantic Analysis of Semantic Graph Databases

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Joslyn, Cliff A.; Adolf, Robert D.; al-Saffar, Sinan; Feo, John T.; Haglin, David J.; Mackey, Greg E.; Mizell, David W.

2011-06-02

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 understand their inherent semantic structure, whether codified in explicit ontologies or not. Our group is researching novel methods for what we call descriptive semantic analysis of RDF triplestores, to serve purposes of analysis, interpretation, visualization, and optimization. But data size and computational complexity makes it increasingly necessary to bring high performance computational resources to bear on this task. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multi-threaded architecture of the Cray XMT platform, conventional servers, and large data stores. In this paper we describe that architecture and our methods, and present the results of our analyses of basic properties, connected components, namespace interaction, and typed paths such for the Billion Triple Challenge 2010 dataset.

Episodic memory, semantic memory, and amnesia.

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Squire, L R; Zola, S M

1998-01-01

Episodic memory and semantic memory are two types of declarative memory. There have been two principal views about how this distinction might be reflected in the organization of memory functions in the brain. One view, that episodic memory and semantic memory are both dependent on the integrity of medial temporal lobe and midline diencephalic structures, predicts that amnesic patients with medial temporal lobe/diencephalic damage should be proportionately impaired in both episodic and semantic memory. An alternative view is that the capacity for semantic memory is spared, or partially spared, in amnesia relative to episodic memory ability. This article reviews two kinds of relevant data: 1) case studies where amnesia has occurred early in childhood, before much of an individual's semantic knowledge has been acquired, and 2) experimental studies with amnesic patients of fact and event learning, remembering and knowing, and remote memory. The data provide no compelling support for the view that episodic and semantic memory are affected differently in medial temporal lobe/diencephalic amnesia. However, episodic and semantic memory may be dissociable in those amnesic patients who additionally have severe frontal lobe damage.

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

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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.

Neural correlates of semantic and syntactic processes in the comprehension of case marked pronouns: Evidence from German and Dutch

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Hammer Anke

2006-03-01

Full Text Available Abstract Background It is well known that both semantic and syntactic information play a role in pronoun resolution in sentences. However, it is unclear what the relative contribution of these sources of information is for the establishment of a coreferential relationship between the pronoun and the antecedent in combination with a local structural case constraint on the pronoun (i.e. case assignment of a pronoun under preposition governing. In a prepositional phrase in German and Dutch, it is the preposition that assigns case to the pronoun. Furthermore, in these languages different overtly case-marked pronouns are used to refer to male and female persons. Thus, one can manipulate biological/syntactic gender features separately from case marking features. The major aim of this study was to determine what the influence of gender information in combination with a local structural case constraint is on the processing of a personal pronoun in a sentence. Event-related brain potential (ERP experiments were performed in German and in Dutch. In a word by word sentence reading study in German and Dutch, gender congruency between the antecedent and the pronoun was manipulated and/or case assignment by the preposition was violated while ERPs of young native speakers were recorded. Results The German and the Dutch ERP data showed an enlarged negativity broadly distributed starting approximately 350 ms after onset of the pronoun followed by a late positivity for gender violations. For syntactic incongruencies without gender violations only a positivity was present. The Dutch data showed an earlier onset of the positivity in comparison to German. Conclusion Finding negativities and positivities for conditions with a gender violation indicates that pronoun resolution with gender incongruency between the pronoun and the antecedent suffers from semantic as well as syntactic integration problems. The presence of a positivity for the syntactically incongruent

Analogical reasoning and prefrontal cortex: evidence for separable retrieval and integration mechanisms.

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Bunge, Silvia A; Wendelken, Carter; Badre, David; Wagner, Anthony D

2005-03-01

The present study examined the contributions of prefrontal cortex (PFC) subregions to two component processes underlying verbal analogical reasoning: semantic retrieval and integration. Event-related functional magnetic resonance imaging data were acquired while subjects performed propositional analogy and semantic decision tasks. On each trial, subjects viewed a pair of words (pair 1), followed by an instructional cue and a second word pair (pair 2). On analogy trials, subjects evaluated whether pair 2 was semantically analogous to pair 1. On semantic trials, subjects indicated whether the pair 2 words were semantically related to each other. Thus, analogy--but not semantic--trials required integration across multiple retrieved relations. To identify regions involved in semantic retrieval, we manipulated the associative strength of pair 1 words in both tasks. Anterior left inferior PFC (aLIPC) was modulated by associative strength, consistent with a role in controlled semantic retrieval. Left frontopolar cortex was insensitive to associative strength, but was more sensitive to integration demands than was aLIPC, consistent with a role in integrating the products of semantic retrieval to evaluate whether distinct representations are analogous. Right dorsolateral PFC exhibited a profile consistent with a role in response selection rather than retrieval or integration. These findings indicate that verbal analogical reasoning depends on multiple, PFC-mediated computations.

Situated conceptualization and semantic processing: effects of emotional experience and context availability in semantic categorization and naming tasks.

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Moffat, Michael; Siakaluk, Paul D; Sidhu, David M; Pexman, Penny M

2015-04-01

It has been proposed that much of conceptual knowledge is acquired through situated conceptualization, such that both external (e.g., agents, objects, events) and internal (e.g., emotions, introspections) environments are considered important (Barsalou, 2003). To evaluate this proposal, we characterized two dimensions by which situated conceptualization may be measured and which should have different relevance for abstract and concrete concepts; namely, emotional experience (i.e., the ease with which words evoke emotional experience; Newcombe, Campbell, Siakaluk, & Pexman, 2012) and context availability (i.e., the ease with which words evoke contexts in which their referents may appear; Schwanenflugel & Shoben, 1983). We examined the effects of these two dimensions on abstract and concrete word processing in verbal semantic categorization (VSCT) and naming tasks. In the VSCT, emotional experience facilitated processing of abstract words but inhibited processing of concrete words, whereas context availability facilitated processing of both types of words. In the naming task in which abstract words and concrete words were not blocked by emotional experience, context availability facilitated responding to only the abstract words. In the naming task in which abstract words and concrete words were blocked by emotional experience, emotional experience facilitated responding to only the abstract words, whereas context availability facilitated responding to only the concrete words. These results were observed even with several lexical (e.g., frequency, age of acquisition) and semantic (e.g., concreteness, arousal, valence) variables included in the analyses. As such, the present research suggests that emotional experience and context availability tap into different aspects of situated conceptualization and make unique contributions to the representation and processing of abstract and concrete concepts.

Usage and applications of Semantic Web techniques and technologies to support chemistry research.

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Borkum, Mark I; Frey, Jeremy G

2014-01-01

The drug discovery process is now highly dependent on the management, curation and integration of large amounts of potentially useful data. Semantics are necessary in order to interpret the information and derive knowledge. Advances in recent years have mitigated concerns that the lack of robust, usable tools has inhibited the adoption of methodologies based on semantics. THIS PAPER PRESENTS THREE EXAMPLES OF HOW SEMANTIC WEB TECHNIQUES AND TECHNOLOGIES CAN BE USED IN ORDER TO SUPPORT CHEMISTRY RESEARCH: a controlled vocabulary for quantities, units and symbols in physical chemistry; a controlled vocabulary for the classification and labelling of chemical substances and mixtures; and, a database of chemical identifiers. This paper also presents a Web-based service that uses the datasets in order to assist with the completion of risk assessment forms, along with a discussion of the legal implications and value-proposition for the use of such a service. We have introduced the Semantic Web concepts, technologies, and methodologies that can be used to support chemistry research, and have demonstrated the application of those techniques in three areas very relevant to modern chemistry research, generating three new datasets that we offer as exemplars of an extensible portfolio of advanced data integration facilities. We have thereby established the importance of Semantic Web techniques and technologies for meeting Wild's fourth "grand challenge".

Neural Indices of Semantic Processing in Early Childhood Distinguish Eventual Stuttering Persistence and Recovery

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Kreidler, Kathryn; Wray, Amanda Hampton; Usler, Evan; Weber, Christine

2017-01-01

Purpose: Maturation of neural processes for language may lag in some children who stutter (CWS), and event-related potentials (ERPs) distinguish CWS who have recovered from those who have persisted. The current study explores whether ERPs indexing semantic processing may distinguish children who will eventually persist in stuttering…

Emotion processing in the aging brain is modulated by semantic elaboration

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Ritchey, Maureen; Bessette-Symons, Brandy; Hayes, Scott M.; Cabeza, Roberto

2010-01-01

The neural correlates of emotion processing have been shown to vary with age: older adults (OAs) exhibit increased frontal activations and, under some circumstances, decreased amygdala activations relative to young adults (YAs) during emotion processing. Some of these differences are additionally modulated by valence, with age-related biases toward positive versus negative stimuli, and are thought to depend on OAs’ capacity for controlled elaboration. However, the role of semantic elaboration in mediating valence effects in the aging brain has not yet been explicitly tested. In the present study, YAs and OAs were scanned while they viewed negative, neutral, and positive pictures during either a deep, elaborative task or a shallow, perceptual task. FMRI results reveal that emotion-related activity in the amygdala is preserved in aging and insensitive to elaboration demands. This study provides novel evidence that differences in valence processing are modulated by elaboration: relative to YAs, OAs show enhanced activity in the medial prefrontal cortex (PFC) and ventrolateral PFC in response to positive versus negative stimuli, but only during elaborative processing. These positive valence effects are predicted by individual differences in executive function in OAs for the deep but not shallow task. Finally, psychophysiological interaction analyses reveal age effects on valence-dependent functional connectivity between medial PFC and ventral striatum, as well as age and task effects on medial PFC-retrosplenial cortex interactions. Altogether, these findings provide support for the hypothesis that valence shifts in the aging brain are mediated by controlled processes such as semantic elaboration, self-referential processing, and emotion regulation. PMID:20869375

A Semantic Approach to Cross-Disciplinary Research Collaboration

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Laurens De Vocht

2012-11-01

Full Text Available The latest developments in ICT, more specifically Social Media and Web 2.0 tools, facilitate the use of online services in research and education. This is also known as Research 2.0 and Technology Enhanced Learning. Web 2.0 tools are especially useful in cases where experts from different disciplines want to collaborate. We suggest an integrated method that embeds these services in research and learning processes, because it is a laborious task for researchers and learners to check and use all varying types of tools and services. We explain a flexible model that uses state-of-the-art semantic technologies to model both structured and unstructured research data. The research data is extracted from many online resources and Social Media. We implement learning objects as an abstraction of the semantically modeled research data. We propose an environment that improves the scientific research and learning process by allowing researchers to efficiently browse the information and concepts represented as learning objects.

Determinants of famous name processing speed: age of acquisition versus semantic connectedness.

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Smith-Spark, James H; Moore, Viv; Valentine, Tim

2013-02-01

The age of acquisition (AoA) and the amount of biographical information known about celebrities have been independently shown to influence the processing of famous people. In this experiment, we investigated the facilitative contribution of both factors to famous name processing. Twenty-four mature adults participated in a familiarity judgement task, in which the names of famous people were grouped orthogonally by AoA and by the number of bits of biographical information known about them (number of facts known; NoFK). Age of acquisition was found to have a significant effect on both reaction time (RT) and accuracy of response, but NoFK did not. The RT data also revealed a significant AoA×NoFK interaction. The amount of information known about a celebrity played a facilitative role in the processing of late-acquired, but not early-acquired, celebrities. Once AoA is controlled, it would appear that the semantic system ceases to have a significant overall influence on the processing of famous people. The pre-eminence of AoA over semantic connectedness is considered in the light of current theories of AoA and how their influence might interact. Copyright © 2012 Elsevier B.V. All rights reserved.

How and When Accentuation Influences Temporally Selective Attention and Subsequent Semantic Processing during On-Line Spoken Language Comprehension: An ERP Study

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Li, Xiao-qing; Ren, Gui-qin

2012-01-01

An event-related brain potentials (ERP) experiment was carried out to investigate how and when accentuation influences temporally selective attention and subsequent semantic processing during on-line spoken language comprehension, and how the effect of accentuation on attention allocation and semantic processing changed with the degree of…

Imaginal, semantic, and surface-level processing of concrete and abstract words: an electrophysiological investigation.

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West, W C; Holcomb, P J

2000-11-01

Words representing concrete concepts are processed more quickly and efficiently than words representing abstract concepts. Concreteness effects have also been observed in studies using event-related brain potentials (ERPs). The aim of this study was to examine concrete and abstract words using both reaction time (RT) and ERP measurements to determine (1) at what point in the stream of cognitive processing concreteness effects emerge and (2) how different types of cognitive operations influence these concreteness effects. Three groups of subjects performed a sentence verification task in which the final word of each sentence was concrete or abstract. For each group the truthfulness judgment required either (1) image generation, (2) semantic decision, or (3) evaluation of surface characteristics. Concrete and abstract words produced similar RTs and ERPs in the surface task, suggesting that postlexical semantic processing is necessary to elicit concreteness effects. In both the semantic and imagery tasks, RTs were shorter for concrete than for abstract words. This difference was greatest in the imagery task. Also, in both of these tasks concrete words elicited more negative ERPs than abstract words between 300 and 550 msec (N400). This effect was widespread across the scalp and may reflect activation in a linguistic semantic system common to both concrete and abstract words. ERPs were also more negative for concrete than abstract words between 550 and 800 msec. This effect was more frontally distributed and was most evident in the imagery task. We propose that this later anterior effect represents a distinct ERP component (N700) that is sensitive to the use of mental imagery. The N700 may reflect the a access of specific characteristics of the imaged item or activation in a working memory system specific to mental imagery. These results also support the extended dual-coding hypothesis that superior associative connections and the use of mental imagery both contribute

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

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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

Brain oscillatory subsequent memory effects differ in power and long-range synchronization between semantic and survival processing.

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Fellner, Marie-Christin; Bäuml, Karl-Heinz T; Hanslmayr, Simon

2013-10-01

Memory crucially depends on the way information is processed during encoding. Differences in processes during encoding not only lead to differences in memory performance but also rely on different brain networks. Although these assumptions are corroborated by several previous fMRI and ERP studies, little is known about how brain oscillations dissociate between different memory encoding tasks. The present study therefore compared encoding related brain oscillatory activity elicited by two very efficient encoding tasks: a typical deep semantic item feature judgment task and a more elaborative survival encoding task. Subjects were asked to judge words either for survival relevance or for animacy, as indicated by a cue presented prior to the item. This allowed dissociating pre-item activity from item-related activity for both tasks. Replicating prior studies, survival processing led to higher recognition performance than semantic processing. Successful encoding in the semantic condition was reflected by a strong decrease in alpha and beta power, whereas successful encoding in the survival condition was related to increased alpha and beta long-range phase synchrony. Moreover, a pre-item subsequent memory effect in theta power was found which did not vary with encoding condition. These results show that measures of local synchrony (power) and global long range-synchrony (phase synchronization) dissociate between memory encoding processes. Whereas semantic encoding was reflected in decreases in local synchrony, increases in global long range synchrony were related to elaborative survival encoding, presumably reflecting the involvement of a more widespread cortical network in this task. Copyright © 2013 Elsevier Inc. All rights reserved.

To predict or not to predict: influences of task and strategy on the processing of semantic relations.

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Roehm, Dietmar; Bornkessel-Schlesewsky, Ina; Rösler, Frank; Schlesewsky, Matthias

2007-08-01

We report a series of event-related potential experiments designed to dissociate the functionally distinct processes involved in the comprehension of highly restricted lexical-semantic relations (antonyms). We sought to differentiate between influences of semantic relatedness (which are independent of the experimental setting) and processes related to predictability (which differ as a function of the experimental environment). To this end, we conducted three ERP studies contrasting the processing of antonym relations (black-white) with that of related (black-yellow) and unrelated (black-nice) word pairs. Whereas the lexical-semantic manipulation was kept constant across experiments, the experimental environment and the task demands varied: Experiment 1 presented the word pairs in a sentence context of the form The opposite of X is Y and used a sensicality judgment. Experiment 2 used a word pair presentation mode and a lexical decision task. Experiment 3 also examined word pairs, but with an antonymy judgment task. All three experiments revealed a graded N400 response (unrelated > related > antonyms), thus supporting the assumption that semantic associations are processed automatically. In addition, the experiments revealed that, in highly constrained task environments, the N400 gradation occurs simultaneously with a P300 effect for the antonym condition, thus leading to the superficial impression of an extremely "reduced" N400 for antonym pairs. Comparisons across experiments and participant groups revealed that the P300 effect is not only a function of stimulus constraints (i.e., sentence context) and experimental task, but that it is also crucially influenced by individual processing strategies used to achieve successful task performance.

Topological Alterations and Symptom-Relevant Modules in the Whole-Brain Structural Network in Semantic Dementia.

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Ding, Junhua; Chen, Keliang; Zhang, Weibin; Li, Ming; Chen, Yan; Yang, Qing; Lv, Yingru; Guo, Qihao; Han, Zaizhu

2017-01-01

Semantic dementia (SD) is characterized by a selective decline in semantic processing. Although the neuropsychological pattern of this disease has been identified, its topological global alterations and symptom-relevant modules in the whole-brain anatomical network have not been fully elucidated. This study aims to explore the topological alteration of anatomical network in SD and reveal the modules associated with semantic deficits in this disease. We first constructed the whole-brain white-matter networks of 20 healthy controls and 19 patients with SD. Then, the network metrics of graph theory were compared between these two groups. Finally, we separated the network of SD patients into different modules and correlated the structural integrity of each module with the severity of the semantic deficits across patients. The network of the SD patients presented a significantly reduced global efficiency, indicating that the long-distance connections were damaged. The network was divided into the following four distinctive modules: the left temporal/occipital/parietal, frontal, right temporal/occipital, and frontal/parietal modules. The first two modules were associated with the semantic deficits of SD. These findings illustrate the skeleton of the neuroanatomical network of SD patients and highlight the key role of the left temporal/occipital/parietal module and the left frontal module in semantic processing.

Integrating semantic web and software agents : Exchanging RIF and BDI rules

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Gong, Y.; Overbeek, S.J.

2011-01-01

Software agents and rules are both used for creating flexibility. Exchanging rules between Semantic Web and agents can ensure consistency in rules and support easy updating and changing of rules. The Rule Interchange Format (RIF) is a new W3C recommendation Semantic Web standard for exchanging rules

Semantic-Web Technology: Applications at NASA

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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.

MATCHING ALTERNATIVE ADDRESSES: A SEMANTIC WEB APPROACH

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S. Ariannamazi

2015-12-01

Full Text Available Rapid development of crowd-sourcing or volunteered geographic information (VGI provides opportunities for authoritatives that deal with geospatial information. Heterogeneity of multiple data sources and inconsistency of data types is a key characteristics of VGI datasets. The expansion of cities resulted in the growing number of POIs in the OpenStreetMap, a well-known VGI source, which causes the datasets to outdate in short periods of time. These changes made to spatial and aspatial attributes of features such as names and addresses might cause confusion or ambiguity in the processes that require feature’s literal information like addressing and geocoding. VGI sources neither will conform specific vocabularies nor will remain in a specific schema for a long period of time. As a result, the integration of VGI sources is crucial and inevitable in order to avoid duplication and the waste of resources. Information integration can be used to match features and qualify different annotation alternatives for disambiguation. This study enhances the search capabilities of geospatial tools with applications able to understand user terminology to pursuit an efficient way for finding desired results. Semantic web is a capable tool for developing technologies that deal with lexical and numerical calculations and estimations. There are a vast amount of literal-spatial data representing the capability of linguistic information in knowledge modeling, but these resources need to be harmonized based on Semantic Web standards. The process of making addresses homogenous generates a helpful tool based on spatial data integration and lexical annotation matching and disambiguating.

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

Science.gov (United States)

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…

Legal Theory, Sources of Law and the Semantic Web

CERN Document Server

Boer, A

2009-01-01

Attempts to construct an integrated conceptual framework for the application-neutral and problem-neutral representation of sources of law using Semantic Web technology and concepts and some technically straightforward extensions to Semantic Web technology based on established practices found in fielded applications

SemFunSim: a new method for measuring disease similarity by integrating semantic and gene functional association.

Directory of Open Access Journals (Sweden)

Liang Cheng

Full Text Available Measuring similarity between diseases plays an important role in disease-related molecular function research. Functional associations between disease-related genes and semantic associations between diseases are often used to identify pairs of similar diseases from different perspectives. Currently, it is still a challenge to exploit both of them to calculate disease similarity. Therefore, a new method (SemFunSim that integrates semantic and functional association is proposed to address the issue.SemFunSim is designed as follows. First of all, FunSim (Functional similarity is proposed to calculate disease similarity using disease-related gene sets in a weighted network of human gene function. Next, SemSim (Semantic Similarity is devised to calculate disease similarity using the relationship between two diseases from Disease Ontology. Finally, FunSim and SemSim are integrated to measure disease similarity.The high average AUC (area under the receiver operating characteristic curve (96.37% shows that SemFunSim achieves a high true positive rate and a low false positive rate. 79 of the top 100 pairs of similar diseases identified by SemFunSim are annotated in the Comparative Toxicogenomics Database (CTD as being targeted by the same therapeutic compounds, while other methods we compared could identify 35 or less such pairs among the top 100. Moreover, when using our method on diseases without annotated compounds in CTD, we could confirm many of our predicted candidate compounds from literature. This indicates that SemFunSim is an effective method for drug repositioning.

Interactions between mood and the structure of semantic memory: event-related potentials evidence.

Science.gov (United States)

Pinheiro, Ana P; del Re, Elisabetta; Nestor, Paul G; McCarley, Robert W; Gonçalves, Óscar F; Niznikiewicz, Margaret

2013-06-01

Recent evidence suggests that affect acts as modulator of cognitive processes and in particular that induced mood has an effect on the way semantic memory is used on-line. We used event-related potentials (ERPs) to examine affective modulation of semantic information processing under three different moods: neutral, positive and negative. Fifteen subjects read 324 pairs of sentences, after mood induction procedure with 30 pictures of neutral, 30 pictures of positive and 30 pictures of neutral valence: 108 sentences were read in each mood induction condition. Sentences ended with three word types: expected words, within-category violations, and between-category violations. N400 amplitude was measured to the three word types under each mood induction condition. Under neutral mood, a congruency (more negative N400 amplitude for unexpected relative to expected endings) and a category effect (more negative N400 amplitude for between- than to within-category violations) were observed. Also, results showed differences in N400 amplitude for both within- and between-category violations as a function of mood: while positive mood tended to facilitate the integration of unexpected but related items, negative mood made their integration as difficult as unexpected and unrelated items. These findings suggest the differential impact of mood on access to long-term semantic memory during sentence comprehension.

The word processing deficit in semantic dementia: all categories are equal, but some categories are more equal than others.

Science.gov (United States)

Pulvermüller, Friedemann; Cooper-Pye, Elisa; Dine, Clare; Hauk, Olaf; Nestor, Peter J; Patterson, Karalyn

2010-09-01

It has been claimed that semantic dementia (SD), the temporal variant of fronto-temporal dementia, is characterized by an across-the-board deficit affecting all types of conceptual knowledge. We here confirm this generalized deficit but also report differential degrees of impairment in processing specific semantic word categories in a case series of SD patients (N = 11). Within the domain of words with strong visually grounded meaning, the patients' lexical decision accuracy was more impaired for color-related than for form-related words. Likewise, within the domain of action verbs, the patients' performance was worse for words referring to face movements and speech acts than for words semantically linked to actions performed with the hand and arm. Psycholinguistic properties were matched between the stimulus groups entering these contrasts; an explanation for the differential degrees of impairment must therefore involve semantic features of the words in the different conditions. Furthermore, this specific pattern of deficits cannot be captured by classic category distinctions such as nouns versus verbs or living versus nonliving things. Evidence from previous neuroimaging research indicates that color- and face/speech-related words, respectively, draw most heavily on anterior-temporal and inferior-frontal areas, the structures most affected in SD. Our account combines (a) the notion of an anterior-temporal amodal semantic "hub" to explain the profound across-the-board deficit in SD word processing, with (b) a semantic topography model of category-specific circuits whose cortical distributions reflect semantic features of the words and concepts represented.

Intelligence related upper alpha desynchronization in a semantic memory task.

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Doppelmayr, M; Klimesch, W; Hödlmoser, K; Sauseng, P; Gruber, W

2005-07-30

Recent evidence shows that event-related (upper) alpha desynchronization (ERD) is related to cognitive performance. Several studies observed a positive, some a negative relationship. The latter finding, interpreted in terms of the neural efficiency hypothesis, suggests that good performance is associated with a more 'efficient', smaller extent of cortical activation. Other studies found that ERD increases with semantic processing demands and that this increase is larger for good performers. Studies supporting the neural efficiency hypothesis used tasks that do not specifically require semantic processing. Thus, we assume that the lack of semantic processing demands may at least in part be responsible for the reduced ERD. In the present study we measured ERD during a difficult verbal-semantic task. The findings demonstrate that during semantic processing, more intelligent (as compared to less intelligent) subjects exhibited a significantly larger upper alpha ERD over the left hemisphere. We conclude that more intelligent subjects exhibit a more extensive activation in a semantic processing system and suggest that divergent findings regarding the neural efficiency hypotheses are due to task specific differences in semantic processing demands.

Emotion processing in the aging brain is modulated by semantic elaboration.

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Ritchey, Maureen; Bessette-Symons, Brandy; Hayes, Scott M; Cabeza, Roberto

2011-03-01

The neural correlates of emotion processing have been shown to vary with age: older adults (OAs) exhibit increased frontal activations and, under some circumstances, decreased amygdala activations relative to young adults (YAs) during emotion processing. Some of these differences are additionally modulated by valence, with age-related biases toward positive versus negative stimuli, and are thought to depend on OAs' capacity for controlled elaboration. However, the role of semantic elaboration in mediating valence effects in the aging brain has not yet been explicitly tested. In the present study, YAs and OAs were scanned while they viewed negative, neutral, and positive pictures during either a deep, elaborative task or a shallow, perceptual task. fMRI results reveal that emotion-related activity in the amygdala is preserved in aging and insensitive to elaboration demands. This study provides novel evidence that differences in valence processing are modulated by elaboration: relative to YAs, OAs show enhanced activity in the medial prefrontal cortex (PFC) and ventrolateral PFC in response to positive versus negative stimuli, but only during elaborative processing. These positive valence effects are predicted by individual differences in executive function in OAs for the deep but not shallow task. Finally, psychophysiological interaction analyses reveal age effects on valence-dependent functional connectivity between medial PFC and ventral striatum, as well as age and task effects on medial PFC-retrosplenial cortex interactions. Altogether, these findings provide support for the hypothesis that valence shifts in the aging brain are mediated by controlled processes such as semantic elaboration, self-referential processing, and emotion regulation. Copyright © 2010 Elsevier Ltd. All rights reserved.

Advancing translational research with the Semantic Web

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Ruttenberg, Alan; Clark, Tim; Bug, William; Samwald, Matthias; Bodenreider, Olivier; Chen, Helen; Doherty, Donald; Forsberg, Kerstin; Gao, Yong; Kashyap, Vipul; Kinoshita, June; Luciano, Joanne; Marshall, M Scott; Ogbuji, Chimezie; Rees, Jonathan; Stephens, Susie; Wong, Gwendolyn T; Wu, Elizabeth; Zaccagnini, Davide; Hongsermeier, Tonya; Neumann, Eric; Herman, Ivan; Cheung, Kei-Hoi

2007-01-01

Background A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. Results We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. Conclusion Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of

Advancing translational research with the Semantic Web.

Science.gov (United States)

Ruttenberg, Alan; Clark, Tim; Bug, William; Samwald, Matthias; Bodenreider, Olivier; Chen, Helen; Doherty, Donald; Forsberg, Kerstin; Gao, Yong; Kashyap, Vipul; Kinoshita, June; Luciano, Joanne; Marshall, M Scott; Ogbuji, Chimezie; Rees, Jonathan; Stephens, Susie; Wong, Gwendolyn T; Wu, Elizabeth; Zaccagnini, Davide; Hongsermeier, Tonya; Neumann, Eric; Herman, Ivan; Cheung, Kei-Hoi

2007-05-09

A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base

Advancing translational research with the Semantic Web

Directory of Open Access Journals (Sweden)

Marshall M Scott

2007-05-01

Full Text Available Abstract Background A fundamental goal of the U.S. National Institute of Health (NIH "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG, set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. Results We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. Conclusion Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need

Taxonomy, Ontology and Semantics at Johnson Space Center

Science.gov (United States)

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.

LEARNING SEMANTICS-ENHANCED LANGUAGE MODELS APPLIED TO UNSUEPRVISED WSD

Energy Technology Data Exchange (ETDEWEB)

VERSPOOR, KARIN [Los Alamos National Laboratory; LIN, SHOU-DE [Los Alamos National Laboratory

2007-01-29

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 learned 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.

Semantic Dysfunction in Women With Schizotypal Personality Disorder

OpenAIRE

Niznikiewicz, Margaret A.; Shenton, Martha E.; Voglmaier, Martina; Nestor, Paul G.; Dickey, Chandlee C.; Frumin, Melissa; Seidman, Larry J.; Allen, Christopher G.; McCarley, Robert W.

2002-01-01

Objective: This study examined whether early or late processes in semantic networks were abnormal in women with a diagnosis of schizotypal personality disorder. The N400 component of the EEG event-related potentials was used as a probe of semantic processes. Method: Word pairs were presented with short and long stimulus-onset asynchronies to investigate, respectively, early and late semantic processes in 16 women with schizotypal personality disorder and 15 normal female comparison subjects. ...

SEMANTIC WEB SERVICES – DISCOVERY, SELECTION AND COMPOSITION TECHNIQUES

OpenAIRE

Sowmya Kamath S; Ananthanarayana V.S

2013-01-01

Web services are already one of the most important resources on the Internet. As an integrated solution for realizing the vision of the Next Generation Web, semantic web services combine semantic web technology with web service technology, envisioning automated life cycle management of web services. This paper discusses the significance and importance of service discovery & selection to business logic, and the requisite current research in the various phases of the semantic web...

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

Science.gov (United States)

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 �

OlyMPUS - The Ontology-based Metadata Portal for Unified Semantics

Science.gov (United States)

Huffer, E.; Gleason, J. L.

2015-12-01

The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS), funded by the NASA Earth Science Technology Office Advanced Information Systems Technology program, is an end-to-end system designed to support data consumers and data providers, enabling the latter to register their data sets and provision them with the semantically rich metadata that drives the Ontology-Driven Interactive Search Environment for Earth Sciences (ODISEES). OlyMPUS leverages the semantics and reasoning capabilities of ODISEES to provide data producers with a semi-automated interface for producing the semantically rich metadata needed to support ODISEES' data discovery and access services. It integrates the ODISEES metadata search system with multiple NASA data delivery tools to enable data consumers to create customized data sets for download to their computers, or for NASA Advanced Supercomputing (NAS) facility registered users, directly to NAS storage resources for access by applications running on NAS supercomputers. A core function of NASA's Earth Science Division is research and analysis that uses the full spectrum of data products available in NASA archives. Scientists need to perform complex analyses that identify correlations and non-obvious relationships across all types of Earth System phenomena. Comprehensive analytics are hindered, however, by the fact that many Earth science data products are disparate and hard to synthesize. Variations in how data are collected, processed, gridded, and stored, create challenges for data interoperability and synthesis, which are exacerbated by the sheer volume of available data. Robust, semantically rich metadata can support tools for data discovery and facilitate machine-to-machine transactions with services such as data subsetting, regridding, and reformatting. Such capabilities are critical to enabling the research activities integral to NASA's strategic plans. However, as metadata requirements increase and competing standards emerge

Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System

Directory of Open Access Journals (Sweden)

Zhenyu Wu

2017-02-01

Full Text Available Web of Things (WoT facilitates the discovery and interoperability of Internet of Things (IoT devices in a cyber-physical system (CPS. Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN, it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT framework for CPS (SWoT4CPS. SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.

Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System.

Science.gov (United States)

Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang

2017-02-20

Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.

Biomedical semantics in the Semantic Web.

Science.gov (United States)

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.

Hierarchical Semantic Model of Geovideo

Directory of Open Access Journals (Sweden)

XIE Xiao

2015-05-01

Full Text Available The public security incidents were getting increasingly challenging with regard to their new features, including multi-scale mobility, multistage dynamic evolution, as well as spatiotemporal concurrency and uncertainty in the complex urban environment. However, the existing video models, which were used/designed for independent archive or local analysis of surveillance video, have seriously inhibited emergency response to the urgent requirements.Aiming at the explicit representation of change mechanism in video, the paper proposed a novel hierarchical geovideo semantic model using UML. This model was characterized by the hierarchical representation of both data structure and semantics based on the change-oriented three domains (feature domain, process domain and event domain instead of overall semantic description of video streaming; combining both geographical semantics and video content semantics, in support of global semantic association between multiple geovideo data. The public security incidents by video surveillance are inspected as an example to illustrate the validity of this model.

The semantic web in translational medicine: current applications and future directions.

Science.gov (United States)

Machado, Catia M; Rebholz-Schuhmann, Dietrich; Freitas, Ana T; Couto, Francisco M

2015-01-01

Semantic web technologies offer an approach to data integration and sharing, even for resources developed independently or broadly distributed across the web. This approach is particularly suitable for scientific domains that profit from large amounts of data that reside in the public domain and that have to be exploited in combination. Translational medicine is such a domain, which in addition has to integrate private data from the clinical domain with proprietary data from the pharmaceutical domain. In this survey, we present the results of our analysis of translational medicine solutions that follow a semantic web approach. We assessed these solutions in terms of their target medical use case; the resources covered to achieve their objectives; and their use of existing semantic web resources for the purposes of data sharing, data interoperability and knowledge discovery. The semantic web technologies seem to fulfill their role in facilitating the integration and exploration of data from disparate sources, but it is also clear that simply using them is not enough. It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge. All these aspects allow the instantiation of translational medicine at the semantic web-scale, thus resulting in a network of solutions that can share resources for a faster transfer of new scientific results into the clinical practice. The envisioned network of translational medicine solutions is on its way, but it still requires resolving the challenges of sharing protected data and of integrating semantic-driven technologies into the clinical practice. © The Author 2013. Published by Oxford University Press.

Facial and semantic emotional interference: A pilot study on the behavioral and cortical responses to the dual valence association task

Directory of Open Access Journals (Sweden)

Petroni Agustín

2011-04-01

Full Text Available Abstract Background Integration of compatible or incompatible emotional valence and semantic information is an essential aspect of complex social interactions. A modified version of the Implicit Association Test (IAT called Dual Valence Association Task (DVAT was designed in order to measure conflict resolution processing from compatibility/incompatibly of semantic and facial valence. The DVAT involves two emotional valence evaluative tasks which elicits two forms of emotional compatible/incompatible associations (facial and semantic. Methods Behavioural measures and Event Related Potentials were recorded while participants performed the DVAT. Results Behavioural data showed a robust effect that distinguished compatible/incompatible tasks. The effects of valence and contextual association (between facial and semantic stimuli showed early discrimination in N170 of faces. The LPP component was modulated by the compatibility of the DVAT. Conclusions Results suggest that DVAT is a robust paradigm for studying the emotional interference effect in the processing of simultaneous information from semantic and facial stimuli.

Semantic memory processing is enhanced in preadolescents breastfed compared to those formula-fed as infants: An ERP N400 study of sentential semantic congruity

Science.gov (United States)

Studies comparing child cognitive development and brain activity during cognitive functions between children who were fed breast milk (BF), milk formula (MF), or soy formula (SF) have not been reported. We recorded event-related scalp potentials reflecting semantic processing (N400 ERP) from 20 homo...

The Role of Semantic Processing in Reading Japanese Orthographies: An Investigation Using a Script-Switch Paradigm

Science.gov (United States)

Dylman, Alexandra S.; Kikutani, Mariko

2018-01-01

Research on Japanese reading has generally indicated that processing of the logographic script Kanji primarily involves whole-word lexical processing and follows a semantics-to-phonology route, while the two phonological scripts Hiragana and Katakana (collectively called Kana) are processed via a sub-lexical route, and more in a…

A Semantic Sensor Web for Environmental Decision Support Applications

Science.gov (United States)

Gray, Alasdair J. G.; Sadler, Jason; Kit, Oles; Kyzirakos, Kostis; Karpathiotakis, Manos; Calbimonte, Jean-Paul; Page, Kevin; García-Castro, Raúl; Frazer, Alex; Galpin, Ixent; Fernandes, Alvaro A. A.; Paton, Norman W.; Corcho, Oscar; Koubarakis, Manolis; De Roure, David; Martinez, Kirk; Gómez-Pérez, Asunción

2011-01-01

Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England. PMID:22164110

Supporting open collaboration in science through explicit and linked semantic description of processes

Science.gov (United States)

Gil, Yolanda; Michel, Felix; Ratnakar, Varun; Read, Jordan S.; Hauder, Matheus; Duffy, Christopher; Hanson, Paul C.; Dugan, Hilary

2015-01-01

The Web was originally developed to support collaboration in science. Although scientists benefit from many forms of collaboration on the Web (e.g., blogs, wikis, forums, code sharing, etc.), most collaborative projects are coordinated over email, phone calls, and in-person meetings. Our goal is to develop a collaborative infrastructure for scientists to work on complex science questions that require multi-disciplinary contributions to gather and analyze data, that cannot occur without significant coordination to synthesize findings, and that grow organically to accommodate new contributors as needed as the work evolves over time. Our approach is to develop an organic data science framework based on a task-centered organization of the collaboration, includes principles from social sciences for successful on-line communities, and exposes an open science process. Our approach is implemented as an extension of a semantic wiki platform, and captures formal representations of task decomposition structures, relations between tasks and users, and other properties of tasks, data, and other relevant science objects. All these entities are captured through the semantic wiki user interface, represented as semantic web objects, and exported as linked data.

An fMRI study of semantic processing in men with schizophrenia

OpenAIRE

Kubicki, M.; McCarley, R.W.; Nestor, P.G.; Huh, T.; Kikinis, R.; Shenton, M.E.; Wible, C.G.

2003-01-01

As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditi...

Preserved musical semantic memory in semantic dementia.

Science.gov (United States)

Weinstein, Jessica; Koenig, Phyllis; Gunawardena, Delani; McMillan, Corey; Bonner, Michael; Grossman, Murray

2011-02-01

To understand the scope of semantic impairment in semantic dementia. Case study. Academic medical center. A man with semantic dementia, as demonstrated by clinical, neuropsychological, and imaging studies. Music performance and magnetic resonance imaging results. Despite profoundly impaired semantic memory for words and objects due to left temporal lobe atrophy, this semiprofessional musician was creative and expressive in demonstrating preserved musical knowledge. Long-term representations of words and objects in semantic memory may be dissociated from meaningful knowledge in other domains, such as music.

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

Science.gov (United States)

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.

The Image of Political Conflict: Evaluation Semantic Universals in Students’ Individual Mind

OpenAIRE

Virna, Zhanna

2014-01-01

Abstract. The paper is focused on the study of the political conflict image from the perspective of psychosemantics. The integral psychosemantic approach to the political conflict allowed establishing semantic universals viewed as students’ evaluation of the conflict’s image. Among the parameters were active, dangerous, open, rational, moral, close, aggressive, etc. The results of the students’ semantic space study through the semantic differential showed that the semantic constructs of “poli...

COEUS: "semantic web in a box" for biomedical applications.

Science.gov (United States)

Lopes, Pedro; Oliveira, José Luís

2012-12-17

As the "omics" revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope with these computer science demands, biomedical software engineers are adopting emerging semantic web technologies that better suit the life sciences domain. The latter's complex relationships are easily mapped into semantic web graphs, enabling a superior understanding of collected knowledge. Despite increased awareness of semantic web technologies in bioinformatics, their use is still limited. COEUS is a new semantic web framework, aiming at a streamlined application development cycle and following a "semantic web in a box" approach. The framework provides a single package including advanced data integration and triplification tools, base ontologies, a web-oriented engine and a flexible exploration API. Resources can be integrated from heterogeneous sources, including CSV and XML files or SQL and SPARQL query results, and mapped directly to one or more ontologies. Advanced interoperability features include REST services, a SPARQL endpoint and LinkedData publication. These enable the creation of multiple applications for web, desktop or mobile environments, and empower a new knowledge federation layer. The platform, targeted at biomedical application developers, provides a complete skeleton ready for rapid application deployment, enhancing the creation of new semantic information systems. COEUS is available as open source at http://bioinformatics.ua.pt/coeus/.

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

Science.gov (United States)

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.

The processing of semantic relatedness in the brain: Evidence from associative and categorical false recognition effects following transcranial direct current stimulation of the left anterior temporal lobe.

Science.gov (United States)

Díez, Emiliano; Gómez-Ariza, Carlos J; Díez-Álamo, Antonio M; Alonso, María A; Fernandez, Angel

2017-08-01

A dominant view of the role of the anterior temporal lobe (ATL) in semantic memory is that it serves as an integration hub, specialized in the processing of semantic relatedness by way of mechanisms that bind together information from different brain areas to form coherent amodal representations of concepts. Two recent experiments, using brain stimulation techniques along with the Deese-Roediger-McDermott (DRM) paradigm, have found a consistent false memory reduction effect following stimulation of the ATL, pointing to the importance of the ATL in semantic/conceptual processing. To more precisely identify the specific process being involved, we conducted a DRM experiment in which transcranial direct current stimulation (anode/cathode/sham) was applied over the participants' left ATL during the study of lists of words that were associatively related to their non-presented critical words (e.g., rotten, worm, red, tree, liqueur, unripe, cake, food, eden, peel, for the critical item apple) or categorically related (e.g., pear, banana, peach, orange, cantaloupe, watermelon, strawberry, cherry, kiwi, plum, for the same critical item apple). The results showed that correct recognition was not affected by stimulation. However, an interaction between stimulation condition and type of relation for false memories was found, explained by a significant false recognition reduction effect in the anodal condition for associative lists that was not observed for categorical lists. Results are congruent with previous findings and, more importantly, they help to clarify the nature and locus of false memory reduction effects, suggesting a differential role of the left ATL, and providing critical evidence for understanding the creation of semantic relatedness-based memory illusions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Combined use of semantics and metadata to manage Research Data Life Cycle in Environmental Sciences

Science.gov (United States)

Aguilar Gómez, Fernando; de Lucas, Jesús Marco; Pertinez, Esther; Palacio, Aida

2017-04-01

The use of metadata to contextualize datasets is quite extended in Earth System Sciences. There are some initiatives and available tools to help data managers to choose the best metadata standard that fit their use cases, like the DCC Metadata Directory (http://www.dcc.ac.uk/resources/metadata-standards). In our use case, we have been gathering physical, chemical and biological data from a water reservoir since 2010. A well metadata definition is crucial not only to contextualize our own data but also to integrate datasets from other sources like satellites or meteorological agencies. That is why we have chosen EML (Ecological Metadata Language), which integrates many different elements to define a dataset, including the project context, instrumentation and parameters definition, and the software used to process, provide quality controls and include the publication details. Those metadata elements can contribute to help both human and machines to understand and process the dataset. However, the use of metadata is not enough to fully support the data life cycle, from the Data Management Plan definition to the Publication and Re-use. To do so, we need to define not only metadata and attributes but also the relationships between them, so semantics are needed. Ontologies, being a knowledge representation, can contribute to define the elements of a research data life cycle, including DMP, datasets, software, etc. They also can define how the different elements are related between them and how they interact. The first advantage of developing an ontology of a knowledge domain is that they provide a common vocabulary hierarchy (i.e. a conceptual schema) that can be used and standardized by all the agents interested in the domain (either humans or machines). This way of using ontologies is one of the basis of the Semantic Web, where ontologies are set to play a key role in establishing a common terminology between agents. To develop an ontology we are using a graphical tool

Polish Semantic Parser

Directory of Open Access Journals (Sweden)

Agnieszka Grudzinska

2000-01-01

Full Text Available Amount of information transferred by computers grows very rapidly thus outgrowing the average man's capability of reception. It implies computer programs increase in the demand for which would be able to perform an introductory classitication or even selection of information directed to a particular receiver. Due to the complexity of the problem, we restricted it to understanding short newspaper notes. Among many conceptions formulated so far, the conceptual dependency worked out by Roger Schank has been chosen. It is a formal language of description of the semantics of pronouncement integrated with a text understanding algorithm. Substantial part of each text transformation system is a semantic parser of the Polish language. It is a module, which as the first and the only one has an access to the text in the Polish language. lt plays the role of an element, which finds relations between words of the Polish language and the formal registration. It translates sentences written in the language used by people into the language theory. The presented structure of knowledge units and the shape of understanding process algorithms are universal by virtue of the theory. On the other hand the defined knowledge units and the rules used in the algorithms ure only examples because they are constructed in order to understand short newspaper notes.

Data processing

International Nuclear Information System (INIS)

Cousot, P.

1988-01-01

The 1988 progress report of the Data Processing laboratory (Polytechnic School, France), is presented. The laboratory research fields are: the semantics, the tests and the semantic analysis of the codes, the formal calculus, the software applications, the algorithms, the neuron networks and VLSI (Very Large Scale Integration). The investigations concerning the polynomial rings are performed by means of the standard basis approach. Among the research topics, the Pascal codes, the parallel processing, the combinatorial, statistical and asymptotic properties of the fundamental data processing tools, the signal processing and the pattern recognition. The published papers, the congress communications and the thesis are also included [fr

A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains.

Science.gov (United States)

Sinaci, A Anil; Laleci Erturkmen, Gokce B

2013-10-01

In order to enable secondary use of Electronic Health Records (EHRs) by bridging the interoperability gap between clinical care and research domains, in this paper, a unified methodology and the supporting framework is introduced which brings together the power of metadata registries (MDR) and semantic web technologies. We introduce a federated semantic metadata registry framework by extending the ISO/IEC 11179 standard, and enable integration of data element registries through Linked Open Data (LOD) principles where each Common Data Element (CDE) can be uniquely referenced, queried and processed to enable the syntactic and semantic interoperability. Each CDE and their components are maintained as LOD resources enabling semantic links with other CDEs, terminology systems and with implementation dependent content models; hence facilitating semantic search, much effective reuse and semantic interoperability across different application domains. There are several important efforts addressing the semantic interoperability in healthcare domain such as IHE DEX profile proposal, CDISC SHARE and CDISC2RDF. Our architecture complements these by providing a framework to interlink existing data element registries and repositories for multiplying their potential for semantic interoperability to a greater extent. Open source implementation of the federated semantic MDR framework presented in this paper is the core of the semantic interoperability layer of the SALUS project which enables the execution of the post marketing safety analysis studies on top of existing EHR systems. Copyright © 2013 Elsevier Inc. All rights reserved.

The Processing of Causal and Hierarchical Relations in Semantic Memory as Revealed by N400 and Frontal Negativity.

Directory of Open Access Journals (Sweden)

Xiuling Liang

Full Text Available Most current studies investigating semantic memory have focused on associative (ring-emerald or taxonomic relations (bird-sparrow. Little is known about the question of how causal relations (virus-epidemic are stored and accessed in semantic memory. The goal of this study was to examine the processing of causally related, general associatively related and hierarchically related word pairs when participants were required to evaluate whether pairs of words were related in any way. The ERP data showed that the N400 amplitude (200-500 ms elicited by unrelated related words was more negative than all related words. Furthermore, the late frontal distributed negativity (500-700 ms elicited by causally related words was smaller than hierarchically related words, but not for general associated words. These results suggested the processing of causal relations and hierarchical relations in semantic memory recruited different degrees of cognitive resources, especially for role binding.

Semantics based approach for analyzing disease-target associations.

Science.gov (United States)

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.

Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

Science.gov (United States)

Fox, P.

2012-04-01

The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.

Semantic embodiment, disembodiment or misembodiment? In search of meaning in modules and neuron circuits.

Science.gov (United States)

Pulvermüller, Friedemann

2013-10-01

"Embodied" proposals claim that the meaning of at least some words, concepts and constructions is grounded in knowledge about actions and objects. An alternative "disembodied" position locates semantics in a symbolic system functionally detached from sensorimotor modules. This latter view is not tenable theoretically and has been empirically falsified by neuroscience research. A minimally-embodied approach now claims that action-perception systems may "color", but not represent, meaning; however, such minimal embodiment (misembodiment?) still fails to explain why action and perception systems exert causal effects on the processing of symbols from specific semantic classes. Action perception theory (APT) offers neurobiological mechanisms for "embodied" referential, affective and action semantics along with "disembodied" mechanisms of semantic abstraction, generalization and symbol combination, which draw upon multimodal brain systems. In this sense, APT suggests integrative-neuromechanistic explanations of why both sensorimotor and multimodal areas of the human brain differentially contribute to specific facets of meaning and concepts. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

The semantic similarity ensemble

Directory of Open Access Journals (Sweden)

Andrea Ballatore

2013-12-01

Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

Automation and integration of components for generalized semantic markup of electronic medical texts.

Science.gov (United States)

Dugan, J M; Berrios, D C; Liu, X; Kim, D K; Kaizer, H; Fagan, L M

1999-01-01

Our group has built an information retrieval system based on a complex semantic markup of medical textbooks. We describe the construction of a set of web-based knowledge-acquisition tools that expedites the collection and maintenance of the concepts required for text markup and the search interface required for information retrieval from the marked text. In the text markup system, domain experts (DEs) identify sections of text that contain one or more elements from a finite set of concepts. End users can then query the text using a predefined set of questions, each of which identifies a subset of complementary concepts. The search process matches that subset of concepts to relevant points in the text. The current process requires that the DE invest significant time to generate the required concepts and questions. We propose a new system--called ACQUIRE (Acquisition of Concepts and Queries in an Integrated Retrieval Environment)--that assists a DE in two essential tasks in the text-markup process. First, it helps her to develop, edit, and maintain the concept model: the set of concepts with which she marks the text. Second, ACQUIRE helps her to develop a query model: the set of specific questions that end users can later use to search the marked text. The DE incorporates concepts from the concept model when she creates the questions in the query model. The major benefit of the ACQUIRE system is a reduction in the time and effort required for the text-markup process. We compared the process of concept- and query-model creation using ACQUIRE to the process used in previous work by rebuilding two existing models that we previously constructed manually. We observed a significant decrease in the time required to build and maintain the concept and query models.

SAS- Semantic Annotation Service for Geoscience resources on the web

Science.gov (United States)

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.

Neural correlates underlying musical semantic memory.

Science.gov (United States)

Groussard, M; Viader, F; Landeau, B; Desgranges, B; Eustache, F; Platel, H

2009-07-01

Numerous functional imaging studies have examined the neural basis of semantic memory mainly using verbal and visuospatial materials. Musical material also allows an original way to explore semantic memory processes. We used PET imaging to determine the neural substrates that underlie musical semantic memory using different tasks and stimuli. The results of three PET studies revealed a greater involvement of the anterior part of the temporal lobe. Concerning clinical observations and our neuroimaging data, the musical lexicon (and most widely musical semantic memory) appears to be sustained by a temporo-prefrontal cerebral network involving right and left cerebral regions.

Semantic annotation in biomedicine: the current landscape.

Science.gov (United States)

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.

The surplus value of semantic annotations

NARCIS (Netherlands)

Marx, M.

2010-01-01

We compare the costs of semantic annotation of textual documents to its benefits for information processing tasks. Semantic annotation can improve the performance of retrieval tasks and facilitates an improved search experience through faceted search, focused retrieval, better document summaries,

Somatotopic Semantic Priming and Prediction in the Motor System

Science.gov (United States)

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

The role of the left anterior temporal lobe in semantic composition vs. semantic memory.

Science.gov (United States)

Westerlund, Masha; Pylkkänen, Liina

2014-05-01

The left anterior temporal lobe (LATL) is robustly implicated in semantic processing by a growing body of literature. However, these results have emerged from two distinct bodies of work, addressing two different processing levels. On the one hand, the LATL has been characterized as a 'semantic hub׳ that binds features of concepts across a distributed network, based on results from semantic dementia and hemodynamic findings on the categorization of specific compared to basic exemplars. On the other, the LATL has been implicated in combinatorial operations in language, as shown by increased activity in this region associated with the processing of sentences and of basic phrases. The present work aimed to reconcile these two literatures by independently manipulating combination and concept specificity within a minimal MEG paradigm. Participants viewed simple nouns that denoted either low specificity (fish) or high specificity categories (trout) presented in either combinatorial (spotted fish/trout) or non-combinatorial contexts (xhsl fish/trout). By combining these paradigms from the two literatures, we directly compared the engagement of the LATL in semantic memory vs. semantic composition. Our results indicate that although noun specificity subtly modulates the LATL activity elicited by single nouns, it most robustly affects the size of the composition effect when these nouns are adjectivally modified, with low specificity nouns eliciting a much larger effect. We conclude that these findings are compatible with an account in which the specificity and composition effects arise from a shared mechanism of meaning specification. Copyright © 2014 Elsevier Ltd. All rights reserved.

Tracking lexical consolidation with ERPs: Lexical and semantic-priming effects on N400 and LPC responses to newly-learned words.

Science.gov (United States)

Bakker, Iske; Takashima, Atsuko; van Hell, Janet G; Janzen, Gabriele; McQueen, James M

2015-12-01

Novel words can be recalled immediately and after little exposure, but require a post-learning consolidation period to show word-like behaviour such as lexical competition. This pattern is thought to reflect a qualitative shift from episodic to lexical representations. However, several studies have reported immediate effects of meaningful novel words on semantic processing, suggesting that integration of novel word meanings may not require consolidation. The current study synthesises and extends these findings by showing a dissociation between lexical and semantic effects on the electrophysiological (N400, LPC) response to novel words. The difference in N400 amplitude between novel and existing words (a lexical effect) decreased significantly after a 24-h consolidation period, providing novel support for the hypothesis that offline consolidation aids lexicalisation. In contrast, novel words preceded by semantically related primes elicited a more positive LPC response (a semantic-priming effect) both before and after consolidation, indicating that certain semantic effects can be observed even when words have not been fully lexicalised. We propose that novel meanings immediately start to contribute to semantic processing, but that the underlying neural processes may shift from strategic to more automatic with consolidation. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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 Neighborhood Effects for Abstract versus Concrete Words.

Science.gov (United States)

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.

Episodic grammar: a computational model of the interaction between episodic and semantic memory in language processing

NARCIS (Netherlands)

Borensztajn, G.; Zuidema, W.; Carlson, L.; Hoelscher, C.; Shipley, T.F.

2011-01-01

We present a model of the interaction of semantic and episodic memory in language processing. Our work shows how language processing can be understood in terms of memory retrieval. We point out that the perceived dichotomy between rule-based versus exemplar-based language modelling can be

Semantic Advertising

OpenAIRE

Zamanzadeh, Ben; Ashish, Naveen; Ramakrishnan, Cartic; Zimmerman, John

2013-01-01

We present the concept of Semantic Advertising which we see as the future of online advertising. Semantic Advertising is online advertising powered by semantic technology which essentially enables us to represent and reason with concepts and the meaning of things. This paper aims to 1) Define semantic advertising, 2) Place it in the context of broader and more widely used concepts such as the Semantic Web and Semantic Search, 3) Provide a survey of work in related areas such as context matchi...

A Case Study in Integrating Multiple E-commerce Standards via Semantic Web Technology

Science.gov (United States)

Yu, Yang; Hillman, Donald; Setio, Basuki; Heflin, Jeff

Internet business-to-business transactions present great challenges in merging information from different sources. In this paper we describe a project to integrate four representative commercial classification systems with the Federal Cataloging System (FCS). The FCS is used by the US Defense Logistics Agency to name, describe and classify all items under inventory control by the DoD. Our approach uses the ECCMA Open Technical Dictionary (eOTD) as a common vocabulary to accommodate all different classifications. We create a semantic bridging ontology between each classification and the eOTD to describe their logical relationships in OWL DL. The essential idea is that since each classification has formal definitions in a common vocabulary, we can use subsumption to automatically integrate them, thus mitigating the need for pairwise mappings. Furthermore our system provides an interactive interface to let users choose and browse the results and more importantly it can translate catalogs that commit to these classifications using compiled mapping results.

Linking Disparate Datasets of the Earth Sciences with the SemantEco Annotator

Science.gov (United States)

Seyed, P.; Chastain, K.; McGuinness, D. L.

2013-12-01

Use of Semantic Web technologies for data management in the Earth sciences (and beyond) has great potential but is still in its early stages, since the challenges of translating data into a more explicit or semantic form for immediate use within applications has not been fully addressed. In this abstract we help address this challenge by introducing the SemantEco Annotator, which enables anyone, regardless of expertise, to semantically annotate tabular Earth Science data and translate it into linked data format, while applying the logic inherent in community-standard vocabularies to guide the process. The Annotator was conceived under a desire to unify dataset content from a variety of sources under common vocabularies, for use in semantically-enabled web applications. Our current use case employs linked data generated by the Annotator for use in the SemantEco environment, which utilizes semantics to help users explore, search, and visualize water or air quality measurement and species occurrence data through a map-based interface. The generated data can also be used immediately to facilitate discovery and search capabilities within 'big data' environments. The Annotator provides a method for taking information about a dataset, that may only be known to its maintainers, and making it explicit, in a uniform and machine-readable fashion, such that a person or information system can more easily interpret the underlying structure and meaning. Its primary mechanism is to enable a user to formally describe how columns of a tabular dataset relate and/or describe entities. For example, if a user identifies columns for latitude and longitude coordinates, we can infer the data refers to a point that can be plotted on a map. Further, it can be made explicit that measurements of 'nitrate' and 'NO3-' are of the same entity through vocabulary assignments, thus more easily utilizing data sets that use different nomenclatures. The Annotator provides an extensive and searchable

Grammaticalization and Semantic Maps: Evidence from Artificial Language

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Remi van Trijp

2010-01-01

Full Text Available Semantic maps have offered linguists an appealing and empirically rooted methodology for describing recurrent structural patterns in language development and the multifunctionality of grammatical categories. Although some researchers argue that semantic maps are universal and given, others provide evidence that there are no fixed or universal maps. This paper takes the position that semantic maps are a useful way to visualize the grammatical evolution of a language (particularly the evolution of semantic structuring but that this grammatical evolution is a consequence of distributed processes whereby language users shape and reshape their language. So it is a challenge to find out what these processes are and whether they indeed generate the kind of semantic maps observed for human languages. This work takes a design stance towards the question of the emergence of linguistic structure and investigates how grammar can be formed in populations of autonomous artificial ?agents? that play ?language games? with each other about situations they perceive through a sensori-motor embodiment. The experiments reported here investigate whether semantic maps for case markers could emerge through grammaticalization processes without the need for a universal conceptual space.

Linking somatic and symbolic representation in semantic memory: the dynamic multilevel reactivation framework.

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Reilly, Jamie; Peelle, Jonathan E; Garcia, Amanda; Crutch, Sebastian J

2016-08-01

Biological plausibility is an essential constraint for any viable model of semantic memory. Yet, we have only the most rudimentary understanding of how the human brain conducts abstract symbolic transformations that underlie word and object meaning. Neuroscience has evolved a sophisticated arsenal of techniques for elucidating the architecture of conceptual representation. Nevertheless, theoretical convergence remains elusive. Here we describe several contrastive approaches to the organization of semantic knowledge, and in turn we offer our own perspective on two recurring questions in semantic memory research: (1) to what extent are conceptual representations mediated by sensorimotor knowledge (i.e., to what degree is semantic memory embodied)? (2) How might an embodied semantic system represent abstract concepts such as modularity, symbol, or proposition? To address these questions, we review the merits of sensorimotor (i.e., embodied) and amodal (i.e., disembodied) semantic theories and address the neurobiological constraints underlying each. We conclude that the shortcomings of both perspectives in their extreme forms necessitate a hybrid middle ground. We accordingly propose the Dynamic Multilevel Reactivation Framework-an integrative model predicated upon flexible interplay between sensorimotor and amodal symbolic representations mediated by multiple cortical hubs. We discuss applications of the dynamic multilevel reactivation framework to abstract and concrete concept representation and describe how a multidimensional conceptual topography based on emotion, sensation, and magnitude can successfully frame a semantic space containing meanings for both abstract and concrete words. The consideration of 'abstract conceptual features' does not diminish the role of logical and/or executive processing in activating, manipulating and using information stored in conceptual representations. Rather, it proposes that the materials upon which these processes operate

A Machine Learning Based Analytical Framework for Semantic Annotation Requirements

OpenAIRE

Hamed Hassanzadeh; MohammadReza Keyvanpour

2011-01-01

The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as ...

Processing lexical semantic and syntactic information in first and second language: fMRI evidence from German and Russian.

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Rüschemeyer, Shirley-Ann; Fiebach, Christian J; Kempe, Vera; Friederici, Angela D

2005-06-01

We introduce two experiments that explored syntactic and semantic processing of spoken sentences by native and non-native speakers. In the first experiment, the neural substrates corresponding to detection of syntactic and semantic violations were determined in native speakers of two typologically different languages using functional magnetic resonance imaging (fMRI). The results show that the underlying neural response of participants to stimuli across different native languages is quite similar. In the second experiment, we investigated how non-native speakers of a language process the same stimuli presented in the first experiment. First, the results show a more similar pattern of increased activation between native and non-native speakers in response to semantic violations than to syntactic violations. Second, the non-native speakers were observed to employ specific portions of the frontotemporal language network differently from those employed by native speakers. These regions included the inferior frontal gyrus (IFG), superior temporal gyrus (STG), and subcortical structures of the basal ganglia.

The Influence of Semantic Neighbours on Visual Word Recognition

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Yates, Mark

2012-01-01

Although it is assumed that semantics is a critical component of visual word recognition, there is still much that we do not understand. One recent way of studying semantic processing has been in terms of semantic neighbourhood (SN) density, and this research has shown that semantic neighbours facilitate lexical decisions. However, it is not clear…

Semantic Information Modeling for Emerging Applications in Smart Grid

Energy Technology Data Exchange (ETDEWEB)

Zhou, Qunzhi; Natarajan, Sreedhar; Simmhan, Yogesh; Prasanna, Viktor

2012-04-16

Smart Grid modernizes power grid by integrating digital and information technologies. Millions of smart meters, intelligent appliances and communication infrastructures are under deployment allowing advanced IT applications to be developed to secure and manage power grid operations. Demand response (DR) is one such emerging application to optimize electricity demand by curtailing/shifting power load when peak load occurs. Existing DR approaches are mostly based on static plans such as pricing policies and load shedding schedules. However, improvements to power management applications rely on data emanating from existing and new information sources with the growth of Smart Grid information space. In particular, dynamic DR algorithms depend on information from smart meters that report interval-based power consumption measurement, HVAC systems that monitor buildings heat and humidity, and even weather forecast services. In order for emerging Smart Grid applications to take advantage of the diverse data influx, extensible information integration is required. In this paper, we develop an integrated Smart Grid information model using Semantic Web techniques and present case studies of using semantic information for dynamic DR. We show the semantic model facilitates information integration and knowledge representation for developing the next generation Smart Grid applications.

Varieties of semantic cognition revealed through simultaneous decomposition of intrinsic brain connectivity and behaviour.

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Vatansever, Deniz; Bzdok, Danilo; Wang, Hao-Ting; Mollo, Giovanna; Sormaz, Mladen; Murphy, Charlotte; Karapanagiotidis, Theodoros; Smallwood, Jonathan; Jefferies, Elizabeth

2017-09-01

Contemporary theories assume that semantic cognition emerges from a neural architecture in which different component processes are combined to produce aspects of conceptual thought and behaviour. In addition to the state-level, momentary variation in brain connectivity, individuals may also differ in their propensity to generate particular configurations of such components, and these trait-level differences may relate to individual differences in semantic cognition. We tested this view by exploring how variation in intrinsic brain functional connectivity between semantic nodes in fMRI was related to performance on a battery of semantic tasks in 154 healthy participants. Through simultaneous decomposition of brain functional connectivity and semantic task performance, we identified distinct components of semantic cognition at rest. In a subsequent validation step, these data-driven components demonstrated explanatory power for neural responses in an fMRI-based semantic localiser task and variation in self-generated thoughts during the resting-state scan. Our findings showed that good performance on harder semantic tasks was associated with relative segregation at rest between frontal brain regions implicated in controlled semantic retrieval and the default mode network. Poor performance on easier tasks was linked to greater coupling between the same frontal regions and the anterior temporal lobe; a pattern associated with deliberate, verbal thematic thoughts at rest. We also identified components that related to qualities of semantic cognition: relatively good performance on pictorial semantic tasks was associated with greater separation of angular gyrus from frontal control sites and greater integration with posterior cingulate and anterior temporal cortex. In contrast, good speech production was linked to the separation of angular gyrus, posterior cingulate and temporal lobe regions. Together these data show that quantitative and qualitative variation in semantic

Deficits in Thematic Integration Processes in Broca's and Wernicke's Aphasia

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Nakano, Hiroko; Blumstein, Sheila E.

2004-01-01

This study investigated how normal subjects and Broca's and Wernicke's aphasics integrate thematic information incrementally using syntax, lexical-semantics, and pragmatics in a simple active declarative sentence. Three priming experiments were conducted using an auditory lexical decision task in which subjects made a lexical decision on a…

Examining lateralized semantic access using pictures.

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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.

Towards Semantic Interpretation of Movement Behavior

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Baglioni, M.; Macedo, J.; Renso, C.; Trasarti, R.; Wachowicz, M.

2009-01-01

In this paper we aim at providing a model for the conceptual representation and deductive reasoning of trajectory patterns obtained from mining raw trajectories. This has been achieved by means of a semantic enrichment process, where raw trajectories are enhanced with semantic information and

Situational Awareness Applied to Geology Field Mapping using Integration of Semantic Data and Visualization Techniques

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Houser, P. I. Q.

2017-12-01

21st century earth science is data-intensive, characterized by heterogeneous, sometimes voluminous collections representing phenomena at different scales collected for different purposes and managed in disparate ways. However, much of the earth's surface still requires boots-on-the-ground, in-person fieldwork in order to detect the subtle variations from which humans can infer complex structures and patterns. Nevertheless, field experiences can and should be enabled and enhanced by a variety of emerging technologies. The goal of the proposed research project is to pilot test emerging data integration, semantic and visualization technologies for evaluation of their potential usefulness in the field sciences, particularly in the context of field geology. The proposed project will investigate new techniques for data management and integration enabled by semantic web technologies, along with new techniques for augmented reality that can operate on such integrated data to enable in situ visualization in the field. The research objectives include: Develop new technical infrastructure that applies target technologies to field geology; Test, evaluate, and assess the technical infrastructure in a pilot field site; Evaluate the capabilities of the systems for supporting and augmenting field science; and Assess the generality of the system for implementation in new and different types of field sites. Our hypothesis is that these technologies will enable what we call "field science situational awareness" - a cognitive state formerly attained only through long experience in the field - that is highly desirable but difficult to achieve in time- and resource-limited settings. Expected outcomes include elucidation of how, and in what ways, these technologies are beneficial in the field; enumeration of the steps and requirements to implement these systems; and cost/benefit analyses that evaluate under what conditions the investments of time and resources are advisable to construct

Categorizing words through semantic memory navigation

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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.

Continuation-like semantics for modeling structural process anomalies

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Grewe Niels

2012-09-01

Full Text Available Abstract Background Biomedical ontologies usually encode knowledge that applies always or at least most of the time, that is in normal circumstances. But for some applications like phenotype ontologies it is becoming increasingly important to represent information about aberrations from a norm. These aberrations may be modifications of physiological structures, but also modifications of biological processes. Methods To facilitate precise definitions of process-related phenotypes, such as delayed eruption of the primary teeth or disrupted ocular pursuit movements, I introduce a modeling approach that draws inspiration from the use of continuations in the analysis of programming languages and apply a similar idea to ontological modeling. This approach characterises processes by describing their outcome up to a certain point and the way they will continue in the canonical case. Definitions of process types are then given in terms of their continuations and anomalous phenotypes are defined by their differences to the canonical definitions. Results The resulting model is capable of accurately representing structural process anomalies. It allows distinguishing between different anomaly kinds (delays, interruptions, gives identity criteria for interrupted processes, and explains why normal and anomalous process instances can be subsumed under a common type, thus establishing the connection between canonical and anomalous process-related phenotypes. Conclusion This paper shows how to to give semantically rich definitions of process-related phenotypes. These allow to expand the application areas of phenotype ontologies beyond literature annotation and establishment of genotype-phenotype associations to the detection of anomalies in suitably encoded datasets.

Acoustic and semantic interference effects in words and pictures.

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Dhawan, M; Pellegrino, J W

1977-05-01

Interference effects for pictures and words were investigated using a probe-recall task. Word stimuli showed acoustic interference effects for items at the end of the list and semantic interference effects for items at the beginning of the list, similar to results of Kintsch and Buschke (1969). Picture stimuli showed large semantic interference effects at all list positions with smaller acoustic interference effects. The results were related to latency data on picture-word processing and interpreted in terms of the differential order, probability, and/or speed of access to acoustic and semantic levels of processing. A levels of processing explanation of picture-word retention differences was related to dual coding theory. Both theoretical positions converge on an explanation of picture-word retention differences as a function of the relative capacity for semantic or associative processing.

The Decoration Operator: A Foundation for On-Line Dimensional Data Integration

DEFF Research Database (Denmark)

Pedersen, Dennis; Pedersen, Torben Bach; Riis, Karsten

2004-01-01

The changing data requirements of today's dynamic business environments are not handled well by current On-Line Analytical Processing (OLAP) systems. Physically integrating unexpected, external data into OLAP cubes, i.e., the data warehousing approach, is a long and time-consuming process, making...... logical, on-the-fly, integration the better choice in many situations. However, OLAP systems have no operations for integrating existing multidimensional cube data with external data. In this paper we present a novel multidimensional algebra operator, the decoration operator, which allows external data...... to be integrated in OLAP cubes as new dimensions, i.e., the cube is ``decorated'' with new dimensions which can subsequently be used just as the regular dimensions. We formally specify the semantics of the decoration operator, ensuring that semantic problems do not occur in the data integration process. We also...

Modulation of Task Demands Suggests That Semantic Processing Interferes with the Formation of Episodic Associations

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Long, Nicole M.; Kahana, Michael J.

2017-01-01

Although episodic and semantic memory share overlapping neural mechanisms, it remains unclear how our pre-existing semantic associations modulate the formation of new, episodic associations. When freely recalling recently studied words, people rely on both episodic and semantic associations, shown through temporal and semantic clustering of…

Data Cleaning and Semantic Improvement in Biological Databases

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Apiletti Daniele

2006-12-01

Full Text Available Public genomic and proteomic databases can be affected by a variety of errors. These errors may involve either the description or the meaning of data (namely, syntactic or semantic errors. We focus our analysis on the detection of semantic errors, in order to verify the accuracy of the stored information. In particular, we address the issue of data constraints and functional dependencies among attributes in a given relational database. Constraints and dependencies show semantics among attributes in a database schema and their knowledge may be exploited to improve data quality and integration in database design, and to perform query optimization and dimensional reduction.

Semantic Priming for Coordinate Distant Concepts in Alzheimer's Disease Patients

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Perri, R.; Zannino, G. D.; Caltagirone, C.; Carlesimo, G. A.

2011-01-01

Semantic priming paradigms have been used to investigate semantic knowledge in patients with Alzheimer's disease (AD). While priming effects produced by prime-target pairs with associative relatedness reflect processes at both lexical and semantic levels, priming effects produced by words that are semantically related but not associated should…

GRAPHIC REALIZATION FOUNDATIONS OF LOGIC-SEMANTIC MODELING IN DIDACTICS

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V. E. Steinberg

2017-01-01

.Practical significance. In-line integration of logic-semantic models into educational process intensifies the process of thinking; it helps on performing of the subject and fact-finding, analytic-speech, modeling- fixative educational activity; also, promotes implementation of invariant forms of education. The examples of use of new didactic means in student teaching are given. In particular, based on the presented didactic means, the didactic multidimensional technology is developed and original computer tutorial DMT-AutoTutor program is designed. 

Semantic Web repositories for genomics data using the eXframe platform.

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Merrill, Emily; Corlosquet, Stéphane; Ciccarese, Paolo; Clark, Tim; Das, Sudeshna

2014-01-01

With the advent of inexpensive assay technologies, there has been an unprecedented growth in genomics data as well as the number of databases in which it is stored. In these databases, sample annotation using ontologies and controlled vocabularies is becoming more common. However, the annotation is rarely available as Linked Data, in a machine-readable format, or for standardized queries using SPARQL. This makes large-scale reuse, or integration with other knowledge bases very difficult. To address this challenge, we have developed the second generation of our eXframe platform, a reusable framework for creating online repositories of genomics experiments. This second generation model now publishes Semantic Web data. To accomplish this, we created an experiment model that covers provenance, citations, external links, assays, biomaterials used in the experiment, and the data collected during the process. The elements of our model are mapped to classes and properties from various established biomedical ontologies. Resource Description Framework (RDF) data is automatically produced using these mappings and indexed in an RDF store with a built-in Sparql Protocol and RDF Query Language (SPARQL) endpoint. Using the open-source eXframe software, institutions and laboratories can create Semantic Web repositories of their experiments, integrate it with heterogeneous resources and make it interoperable with the vast Semantic Web of biomedical knowledge.

Automaticity Revisited: When Print Doesn't Activate Semantics

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Elsa Magdalena Labuschagne

2015-02-01

Full Text Available It is widely accepted that the presentation of a printed word automatically triggers processing that ends with full semantic activation. This processing, among other characteristics, is held to occur without intention, and cannot be stopped. The results of the present experiment show that this account is problematic in the context of a variant of the Stroop paradigm. Subjects named the print color of words that were either neutral or semantically related to color. When the letters were all colored, all spatially cued, and the spaces between letters were filled with characters from the top of the keyboard (i.e., 4, #, 5, %, 6, and *, color naming yielded a semantically based Stroop effect and a semantically based negative priming effect. In contrast, the same items yielded neither a semantic Stroop effect nor a negative priming effect when a single target letter was uniquely colored and spatially cued. These findings undermine the widespread view that lexical-semantic activation in word reading is automatic in the sense that it occurs without intention and cannot be derailed.

Automatic and directed search processes in solving simple semantic-memory problems.

Science.gov (United States)

Ben-Zur, H

1989-09-01

The cognitive processes involved in simple semantic-memory problems were investigated in four experiments. On each trial of Experiments 1 and 2, two stimulus words were presented, with the instructions to find a third word (i.e., the solution) that, when coupled with each of the stimuli, would yield two word pairs used in everyday language (e.g., surprise and birthday, for which the solution is party). The results of the two experiments indicated that informing the subject whether the solution constituted the first or the second element in the word pairs facilitated both likelihood and speed of solution attainment. In addition, solution attainment was relatively high for items based on frequently used word pairs (Experiment 1) and for items in which the stimuli appear, in everyday language, in a small number of word pairs (Experiment 2). In Experiment 3, the subjects were required to produce word pairs containing one of the two stimulus words from the items used in Experiment 2. Solution production was facilitated by rehearsing the second stimulus word of the specific item. The conclusion, supported by a post hoc analysis of the results of Experiments 2 and 3 (Experiment 4), was that indirect priming from one stimulus word may facilitate solution production from a searched word. These results are interpreted in terms of automatic and controlled processes, and their relevance to two different models for retrieval from semantic memory is discussed.

Knowledge representation and management: towards an integration of a semantic web in daily health practice.

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Griffon, N; Charlet, J; Darmoni, Sj

2013-01-01

To summarize the best papers in the field of Knowledge Representation and Management (KRM). A synopsis of the four selected articles for the IMIA Yearbook 2013 KRM section is provided, as well as highlights of current KRM trends, in particular, of the semantic web in daily health practice. The manual selection was performed in three stages: first a set of 3,106 articles, then a second set of 86 articles followed by a third set of 15 articles, and finally the last set of four chosen articles. Among the four selected articles (see Table 1), one focuses on knowledge engineering to prevent adverse drug events; the objective of the second is to propose mappings between clinical archetypes and SNOMED CT in the context of clinical practice; the third presents an ontology to create a question-answering system; the fourth describes a biomonitoring network based on semantic web technologies. These four articles clearly indicate that the health semantic web has become a part of daily practice of health professionals since 2012. In the review of the second set of 86 articles, the same topics included in the previous IMIA yearbook remain active research fields: Knowledge extraction, automatic indexing, information retrieval, natural language processing, management of health terminologies and ontologies.

Impact of Semantic Relatedness on Associative Memory: An ERP Study

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Pierre Desaunay

2017-06-01

Full Text Available Encoding and retrieval processes in memory for pairs of pictures are thought to be influenced by inter-item similarity and by features of individual items. Using Event-Related Potentials (ERP, we aimed to identify how these processes impact on both the early mid-frontal FN400 and the Late Positive Component (LPC potentials during associative retrieval of pictures. Twenty young adults undertook a sham task, using an incidental encoding of semantically related and unrelated pairs of drawings. At test, we conducted a recognition task in which participants were asked to identify target identical pairs of pictures, which could be semantically related or unrelated, among new and rearranged pairs. We observed semantic (related and unrelated pairs and condition effects (old, rearranged and new pairs on the early mid-frontal potential. First, a lower amplitude was shown for identical and rearranged semantically related pairs, which might reflect a retrieval process driven by semantic cues. Second, among semantically unrelated pairs, we found a larger negativity for identical pairs, compared to rearranged and new ones, suggesting additional retrieval processing that focuses on associative information. We also observed an LPC old/new effect with a mid-parietal and a right occipito-parietal topography for semantically related and unrelated old pairs, demonstrating a recollection phenomenon irrespective of the degree of association. These findings suggest that associative recognition using visual stimuli begins at early stages of retrieval, and differs according to the degree of semantic relatedness among items. However, either strategy may ultimately lead to recollection processes.

Semantic content-based recommendations using semantic graphs.

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Guo, Weisen; Kraines, Steven B

2010-01-01

Recommender systems (RSs) can be useful for suggesting items that might be of interest to specific users. Most existing content-based recommendation (CBR) systems are designed to recommend items based on text content, and the items in these systems are usually described with keywords. However, similarity evaluations based on keywords suffer from the ambiguity of natural languages. We present a semantic CBR method that uses Semantic Web technologies to recommend items that are more similar semantically with the items that the user prefers. We use semantic graphs to represent the items and we calculate the similarity scores for each pair of semantic graphs using an inverse graph frequency algorithm. The items having higher similarity scores to the items that are known to be preferred by the user are recommended.

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

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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

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

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Martin Ulrich

Full Text Available 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.

Atypical temporal activation pattern and central-right brain compensation during semantic judgment task in children with early left brain damage.

Science.gov (United States)

Chang, Yi-Tzu; Lin, Shih-Che; Meng, Ling-Fu; Fan, Yang-Teng

In this study we investigated the event-related potentials (ERPs) during the semantic judgment task (deciding if the two Chinese characters were semantically related or unrelated) to identify the timing of neural activation in children with early left brain damage (ELBD). The results demonstrated that compared with the controls, children with ELBD had (1) competitive accuracy and reaction time in the semantic judgment task, (2) weak operation of the N400, (3) stronger, earlier and later compensational positivities (referred to the enhanced P200, P250, and P600 amplitudes) in the central and right region of the brain to successfully engage in semantic judgment. Our preliminary findings indicate that temporally postlesional reorganization is in accordance with the proposed right-hemispheric organization of speech after early left-sided brain lesion. During semantic processing, the orthography has a greater effect on the children with ELBD, and a later semantic reanalysis (P600) is required due to the less efficient N400 at the former stage for semantic integration. Copyright © 2018 Elsevier Inc. All rights reserved.

The BiSciCol Triplifier: bringing biodiversity data to the Semantic Web.

Science.gov (United States)

Stucky, Brian J; Deck, John; Conlin, Tom; Ziemba, Lukasz; Cellinese, Nico; Guralnick, Robert

2014-07-29

Recent years have brought great progress in efforts to digitize the world's biodiversity data, but integrating data from many different providers, and across research domains, remains challenging. Semantic Web technologies have been widely recognized by biodiversity scientists for their potential to help solve this problem, yet these technologies have so far seen little use for biodiversity data. Such slow uptake has been due, in part, to the relative complexity of Semantic Web technologies along with a lack of domain-specific software tools to help non-experts publish their data to the Semantic Web. The BiSciCol Triplifier is new software that greatly simplifies the process of converting biodiversity data in standard, tabular formats, such as Darwin Core-Archives, into Semantic Web-ready Resource Description Framework (RDF) representations. The Triplifier uses a vocabulary based on the popular Darwin Core standard, includes both Web-based and command-line interfaces, and is fully open-source software. Unlike most other RDF conversion tools, the Triplifier does not require detailed familiarity with core Semantic Web technologies, and it is tailored to a widely popular biodiversity data format and vocabulary standard. As a result, the Triplifier can often fully automate the conversion of biodiversity data to RDF, thereby making the Semantic Web much more accessible to biodiversity scientists who might otherwise have relatively little knowledge of Semantic Web technologies. Easy availability of biodiversity data as RDF will allow researchers to combine data from disparate sources and analyze them with powerful linked data querying tools. However, before software like the Triplifier, and Semantic Web technologies in general, can reach their full potential for biodiversity science, the biodiversity informatics community must address several critical challenges, such as the widespread failure to use robust, globally unique identifiers for biodiversity data.

The Semantics of Web Services: An Examination in GIScience Applications

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Xuan Shi

2013-09-01

Full Text Available Web service is a technological solution for software interoperability that supports the seamless integration of diverse applications. In the vision of web service architecture, web services are described by the Web Service Description Language (WSDL, discovered through Universal Description, Discovery and Integration (UDDI and communicate by the Simple Object Access Protocol (SOAP. Such a divination has never been fully accomplished yet. Although it was criticized that WSDL only has a syntactic definition of web services, but was not semantic, prior initiatives in semantic web services did not establish a correct methodology to resolve the problem. This paper examines the distinction and relationship between the syntactic and semantic definitions for web services that characterize different purposes in service computation. Further, this paper proposes that the semantics of web service are neutral and independent from the service interface definition, data types and platform. Such a conclusion can be a universal law in software engineering and service computing. Several use cases in the GIScience application are examined in this paper, while the formalization of geospatial services needs to be constructed by the GIScience community towards a comprehensive ontology of the conceptual definitions and relationships for geospatial computation. Advancements in semantic web services research will happen in domain science applications.

X-Informatics: Practical Semantic Science

Science.gov (United States)

Borne, K. D.

2009-12-01

The discipline of data science is merging with multiple science disciplines to form new X-informatics research disciplines. They are almost too numerous to name, but they include geoinformatics, bioinformatics, cheminformatics, biodiversity informatics, ecoinformatics, materials informatics, and the emerging discipline of astroinformatics. Within any X-informatics discipline, the information granules are unique to that discipline -- e.g., gene sequences in bio, the sky object in astro, and the spatial object in geo (such as points, lines, and polygons in the vector model, and pixels in the raster model). Nevertheless the goals are similar: transparent data re-use across subdisciplines and within education settings, information and data integration and fusion, personalization of user interactions with the data collection, semantic search and retrieval, and knowledge discovery. The implementation of an X-informatics framework enables these semantic e-science research goals. We describe the concepts, challenges, and new developments associated with the new discipline of astroinformatics, and how geoinformatics provides valuable lessons learned and a model for practical semantic science within a traditional science discipline through the accretion of data science methodologies (such as formal metadata creation, data models, data mining, information retrieval, knowledge engineering, provenance, taxonomies, and ontologies). The emerging concept of data-as-a-service (DaaS) builds upon the concept of smart data (or data DNA) for intelligent data management, automated workflows, and intelligent processing. Smart data, defined through X-informatics, enables several practical semantic science use cases, including self-discovery, data intelligence, automatic recommendations, relevance analysis, dimension reduction, feature selection, constraint-based mining, interdisciplinary data re-use, knowledge-sharing, data use in education, and more. We describe these concepts within the

Social Networking on the Semantic Web

Science.gov (United States)

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…

When a hit sounds like a kiss : An electrophysiological exploration of semantic processing in visual narrative

NARCIS (Netherlands)

Manfredi, Mirella; Cohn, Neil; Kutas, Marta

2017-01-01

Researchers have long questioned whether information presented through different sensory modalities involves distinct or shared semantic systems. We investigated uni-sensory cross-modal processing by recording event-related brain potentials to words replacing the climactic event in a visual

MONIL Language, an Alternative for Data Integration

OpenAIRE

Larre, Mónica; Torres-Jiménez, José; Morales, Eduardo; Frausto-Solís, Juan; Torres, Sócrates

2006-01-01

Data integration is a process of retrieving, merging and storing of data originated in heterogeneous sources of data. The main problem facing the data integration is the structural and semantic heterogeneity of participating data. A concern of research communities in computer sciences is the development of semi-automatic tools to assist the user in an effective way in the data integration processes. This paper introduces a programming language called MONIL, as an alternative to integrate data...

A Semantic Sensor Web for Environmental Decision Support Applications

Directory of Open Access Journals (Sweden)

Raúl García-Castro

2011-09-01

Full Text Available Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.

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

Science.gov (United States)

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)…