Search results for "Semantic"

showing 10 items of 941 documents

Semantic aware RSS query algebra

2010

International audience; Existing XML query algebras are not fully appropriate to retrieve RSS news items mainly due to three reasons: 1) RSS is text rich and its content is dependent on the wording and verbification of the author, thus semantic aware operators are needed; 2) news items are dynamic and consequently time oriented retrieval is needed; 3) a news item may evolve through time, or overlap with other news items and hence identifying relationships between items is also needed. In this paper, we aim to solve these issues by providing a dedicated RSS algebra based on semantic-aware operators that consider RSS characteristics. The provided operators are application domain specific and …

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/Webcomputer.internet_protocolComputer scienceRSS[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologyQuery optimizationQuery algebraQuery expansion[SCCO.COMP] Cognitive science/Computer scienceApplication domain020204 information systems0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Equivalence (formal languages)[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]Semantic queryInformation retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]computer.file_format[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]computerXML
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Semantic oriented data structuration for MABS Application to BIM

2013

International audience; This paper presents a multiagent-based simulation approach to qualify the usage of buildings from the design phase. Our approach combines ontology and evolution process based on machine learning algorithms. The ontology relies on semantic data structures for the representation of environment components, agent knowledge and all data generated during the simulation.

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and SimulationComputer scienceProcess (engineering)0211 other engineering and technologies020101 civil engineering02 engineering and technologyOntology (information science)Semantic data modelcomputer.software_genre0201 civil engineering021105 building & constructionUpper ontologyRepresentation (mathematics)business.industryOntology-based data integration[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationDesign phaseBuilding information modeling[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA][ INFO.INFO-MA ] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA][INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationData miningbusinessSoftware engineeringcomputer
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SCALESEM : Evaluation of Semantic Graph based on Model Checking

2011

International audience; Semantic interoperability problems have found their solutions using languages and techniques from the Semantic Web. The proliferation of ontologies and meta-information has improved the understanding of information and the relevance of search engine responses. However, the construction of semantic graphs is a source of numerous errors of interpretation or modelling and scalability remains a major problem. The processing of large semantic graphs is a limit to the use of semantics in current information systems. The work presented in this paper is part of a new research at the border of two areas: the semantic web and the model checking. This line of research concerns …

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and SimulationModel-checking[INFO.INFO-WB] Computer Science [cs]/WebTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMSSemantic graph[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/WebTemporal logic[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationTemporal logic.
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RDF2SPIN: Mapping Semantic Graphs to SPIN Model Checker

2011

International audience; The most frequently used language to represent the semantic graphs is the RDF (W3C standard for meta-modeling). The construction of semantic graphs is a source of numerous errors of interpretation. The processing of large semantic graphs is a limit to the use of semantics in current information systems. The work presented in this paper is part of a new research at the border between two areas: the semantic web and the model checking. For this, we developed a tool, RDF2SPIN, which converts RDF graphs into SPIN language. This conversion aims checking the semantic graphs with the model checker SPIN in order to verify the consistency of the data. To illustrate our propos…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and SimulationTheoretical computer science[INFO.INFO-WB] Computer Science [cs]/WebComputer science0211 other engineering and technologies[ INFO.INFO-WB ] Computer Science [cs]/WebTemporal logic02 engineering and technologyRDF/XMLRDF020204 information systemsSemantic computing021105 building & construction0202 electrical engineering electronic engineering information engineeringSPARQLBIMRDFCwmSemantic WebBIM.Semantic Web Rule Language[INFO.INFO-WB]Computer Science [cs]/WebModel-Checkingcomputer.file_format[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationSPINSemantic graphSemantic technologyIFC[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulationcomputer
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Qualifying semantic graphs using model checking

2011

International audience; Semantic interoperability problems have found their solutions using languages and techniques from the Semantic Web. The proliferation of ontologies and meta-information has improved the understanding of information and the relevance of search engine responses. However, the construction of semantic graphs is a source of numerous errors of interpretation or modeling and scalability remains a major problem. The processing of large semantic graphs is a limit to the use of semantics in current information systems. The work presented in this paper is part of a new research at the border of two areas: the semantic web and the model checking. This line of research concerns t…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation[INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web0102 computer and information sciences02 engineering and technologycomputer.software_genre01 natural sciencesSocial Semantic Webtemporal logicSemantic similaritySemantic computing0202 electrical engineering electronic engineering information engineeringSemantic analyticsSemantic integrationSemantic Web StackInformation retrievalbusiness.industry[INFO.INFO-WB]Computer Science [cs]/WebSemantic search020207 software engineeringSemantic interoperability[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationModel-checking010201 computation theory & mathematicsSemantic graphTheoryofComputation_LOGICSANDMEANINGSOFPROGRAMS[INFO.INFO-MO] Computer Science [cs]/Modeling and SimulationArtificial intelligencebusinesscomputerNatural language processing2011 International Conference on Innovations in Information Technology
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A new approach based on NμSMV Model to query semantic graph

2011

International audience; The language most frequently used to represent the semantic graphs is the RDF (W3C standard for meta-modeling). The construction of semantic graphs is a source of numerous errors of interpretation. Processing of large semantic graphs can be a limit to use semantics in modern information systems. The work presented in this paper is part of a new research at the border between two areas: the semantic web and the model checking. For this, we developed a tool, RDF2NμSMV, which converts RDF graphs into NμSMV language. This conversion aims checking the semantic graphs with the model checker NμSMV in order to verify the consistency of the data. The data integration and shar…

[ INFO.INFO-MO ] Computer Science [cs]/Modeling and Simulation[INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/WebNμSMVTemporal logic02 engineering and technologycomputer.software_genreQuery languageSPARQLtemporal logic queryRDFModel CheckingSemantic similarity020204 information systemsSemantic computing0202 electrical engineering electronic engineering information engineeringSPARQLRDFSemantic WebGraph databaseInformation retrieval[INFO.INFO-WB]Computer Science [cs]/Webcomputer.file_format[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationAbstract semantic graphSemantic graphQuery checking020201 artificial intelligence & image processing[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulationcomputer
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A Context-Based Adaptation In Mobile Learning

2013

International audience; Recent developments on mobile devices and wireless technologies enable new technical capabilities for the learning domain. Nowadays, learners are able to learn anywhere and at any time. The dynamic and continually changing learning setting in learner's mobile environment gives rise to many different learning contexts. The challenge in context-aware mobile learning is to develop an approach building the best learning content according to dynamic learning situations. This paper aims to develop an adaptive system based on the semantic modeling of the learning content and the learning context. The behavioral part of this approach is made up of rules and metaheuristics to…

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC][INFO.INFO-WB] Computer Science [cs]/Web[SHS.EDU]Humanities and Social Sciences/Education[SHS.EDU] Humanities and Social Sciences/Education[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/Web[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC][ SHS.EDU ] Humanities and Social Sciences/Education[ MATH.MATH-CO ] Mathematics [math]/Combinatorics [math.CO]context[MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO]mobile learning[INFO.INFO-MC]Computer Science [cs]/Mobile Computingsemantic web[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[INFO.EIAH] Computer Science [cs]/Technology for Human Learning[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computing[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO][ INFO.EIAH ] Computer Science [cs]/Technology for Human Learning[INFO.EIAH]Computer Science [cs]/Technology for Human Learning[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Adaptation
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The minerality of wine: which status for the lexeme in which situations ?

2014

International audience; This paper aims at discussing the meaning, the relevance, and the status of the lexeme minerality in consumers’ and wine professionals’ discourses within the French-speaking world. It takes as a starting point the obvious role played by such a lexeme in wine tasting notes, in prescriptive texts, and in the marketing sector. Following previous studies [1]-[2] that have shown the instability of the notion for many speakers —including wine professionals— the discussion will focus on the status of this so-called term for each target group.The study is based on the analysis of two sub-corpora collected through a questionnaire addressed on the one hand to consumers and on …

[ SHS ] Humanities and Social Sciences[ SHS.LANGUE ] Humanities and Social Sciences/Linguisticsmineralitydiscourse[SHS] Humanities and Social Sciencesperception[SHS.LANGUE]Humanities and Social Sciences/Linguistics[SHS.LANGUE] Humanities and Social Sciences/Linguisticssemantics[SHS]Humanities and Social Sciences
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Know Beyond Seeing: Combining Computer Vision with Semantic Reasoning

2018

International audience; To date, computer vision systems are limited to extract the digital data of what the cameras "see". However, the meaning of what they observe could be greatly enhanced by considering the environment and common-sense knowledge. A new approach to combine computer vision with semantic modeling has been developed. This approach extracts the knowledge from images and uses it to perform real-time reasoning according to the contextual information, events of interest and logic rules. The reasoning with image knowledge allows protecting the privacy of the users, to overcome some problems of computer vision such as occlusion and missed detections and to offer services such as …

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]0209 industrial biotechnologybusiness.industryComputer scienceDigital data0211 other engineering and technologiesCognition02 engineering and technology[INFO] Computer Science [cs]Semantics[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]020901 industrial engineering & automation021105 building & constructionContextual informationComputer vision[INFO]Computer Science [cs]Artificial intelligenceMeaning (existential)businessAND gateBuilding automation
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Bridging Sensing and Decision Making in Ambient Intelligence Environments

2009

Context-aware and Ambient Intelligence environments represent one of the emerging issues in the last decade. In such intelligent environments, information is gathered to provide, on one hand, autonomic and easy to manage applications, and, on the other, secured access controlled environments. Several approaches have been defined in the literature to describe context-aware application with techniques to capture and represent information related to a specified domain. However and to the best of our knowledge, none has questioned the reliability of the techniques used to extract meaningful knowledge needed for decision making especially if the information captured is of multimedia types (image…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Ambient intelligenceComputer science02 engineering and technologycomputer.software_genreBridging (programming)[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]uncertainty resolver modelHuman–computer interaction020204 information systemsResolver0202 electrical engineering electronic engineering information engineeringcontext-aware applicationsemantic-based020201 artificial intelligence & image processingData mining[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]computer
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