Search results for "Semantic Web"

showing 10 items of 150 documents

Guest Editors' Introduction: Multimedia Metadata and Semantic Management

2009

This special issue assesses the current status and technologies and describes major challenges and proper solutions for effective multimedia production and management related to evolving Semantic Web strategies. The included articles, which cover different facets of the semantic management of multimedia and multimedia metadata from retrieval and processing to consumption and presentation, represent a step forward in research targeted at improving aspects of the semantic metadata life cycle.

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologySemanticsWorld Wide Web[SCCO.COMP] Cognitive science/Computer scienceSemantic computing0202 electrical engineering electronic engineering information engineeringMedia Technology[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Semantic Web StackSemantic WebImage retrieval[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]business.industry[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]020207 software engineeringComputer Science ApplicationsMetadataSemantic grid[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Hardware and Architecture[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Signal Processing020201 artificial intelligence & image processingThe Internet[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]businessSoftware
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Towards a methodology for semantic and context-aware mobile learning

2013

International audience; Internet and mobile devices open the way towards mobile learning (m-learning), offering new opportunities to extend learning beyond the traditional teacher-led classroom. M-learning is not only any form of teaching or studying that takes place when the user interacts with a mobile device. It is more than just using a mobile device to access resources and communicate with others. It should take account of the constant mobile situation of the learner. The challenge here is to exploit this continually changing situation with a system that can dynamically recognize and adapt educational resources and services to the "context" in which the learner operates (localization, …

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebExploitComputer science[ INFO.INFO-IU ] Computer Science [cs]/Ubiquitous Computing[ INFO.INFO-WB ] Computer Science [cs]/WebContext (language use)02 engineering and technologycontextWorld Wide Webmobile learning[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-MC]Computer Science [cs]/Mobile ComputingConstant (computer programming)semantic web[INFO.INFO-MC] Computer Science [cs]/Mobile Computing[ INFO.INFO-MC ] Computer Science [cs]/Mobile Computing0202 electrical engineering electronic engineering information engineeringMobile searchSemantic Webbusiness.industry[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing020206 networking & telecommunicationsOpen learning[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]The Internet[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]businessMobile device
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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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Semantic User Profiling for Digital Advertising

2015

International audience; With the emergence of real-time distribution of online advertising space (“real-time bidding”), user profiling from web navigation traces becomes crucial. Indeed, it allows online advertisers to target customers without interfering with their activities. Current techniques apply traditional methods as statistics and machine learning, but suffer from their limitations. As an answer, the proposed approach aims to develop and evaluate a semantic-based user profiling system for digital advertising.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Data AnalysisBig DataACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.5: Online Information Services[ INFO ] Computer Science [cs]OntologyACM : H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.1: Content Analysis and IndexingACM : H.: Information SystemsUser ProfilingACM: H.: Information Systems/H.4: INFORMATION SYSTEMS APPLICATIONSReasoningACM : H.: Information Systems/H.4: INFORMATION SYSTEMS APPLICATIONS[INFO] Computer Science [cs][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]ACM : H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.4: Systems and Software/H.3.4.5: User profiles and alert servicesACM: H.: Information SystemsInferenceACM : H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.5: Online Information Services[INFO]Computer Science [cs]Logical Rules[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.1: Content Analysis and IndexingSWRLACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.4: Systems and Software/H.3.4.5: User profiles and alert servicesSemantic Web
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FOWLA, A Federated Architecture for Ontologies.

2015

International audience; The progress of information and communication technologies has greatly increased the quantity of data to process. Thus, managing data heterogeneity is a problem nowadays. In the 1980s, the concept of a Federated Database Architecture (FDBA) was introduced as a collection of components to unite loosely coupled federation. Semantic web technologies mitigate the data heterogeneity problem, however due to the data structure heterogeneity the integration of several ontologies is still a complex task. For tackling this problem, we propose a loosely coupled federated ontology architecture (FOWLA). Our approach allows the coexistence of various ontologies sharing common data…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Federated Ontology ArchitectureComputer scienceProcess (engineering)Distributed computing[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Ontology (information science)SPARQL[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]World Wide WebSPARQLArchitecture[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Semantic WebComputingMilieux_MISCELLANEOUSSWRLOWLHorn-like rules[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]computer.file_formatSemantic interoperabilityData structuresemantic interoperabilitybackward-chaining reasoningInformation and Communications Technologycomputer
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How to Enrich Description Logics with Fuzziness

2017

International audience; The paper describes the relation between fuzzy and non-fuzzy description logics. It gives an overview about current research in these areas and describes the difference between tasks for description logics and fuzzy logics. The paper also deals with the transformation properties of description logics to fuzzy logics and backwards. While the process of transformation from a description logic to a fuzzy logic is a trivial inclusion, the other way of reducing information from fuzzy logic to description logic is a difficult task, that will be topic of future work.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Theoretical computer science[ INFO ] Computer Science [cs]Relation (database)Process (engineering)Computer scienceMathematics::General Mathematics0102 computer and information sciences02 engineering and technology[INFO] Computer Science [cs]01 natural sciencesFuzzy logicTask (project management)[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Knowledge-based systemsFuzzy Description LogicDescription logicComputer Science::Logic in Computer Science0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Semantic WebSemantic WebUncertaintyTransformation (function)TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES010201 computation theory & mathematics020201 artificial intelligence & image processingComputingMethodologies_GENERALHardware_LOGICDESIGN
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Integration of Spatial Technologies and Semantic Web Technologies for Industrial Archaeology

2010

International audience; We propose a method that uses the advancement in spatial technologies from current database systems within the Semantic Web Technologies in order to enrich and to populate the knowledge of a domain defined in an OWL-DL ontology. The results of spatial operations and functions are used to populate and to enrich ontologies with new individuals and new relationships. The advantage of spatial analysis within Semantic Web technologies is the diversity of the functionalities provided by the combination of spatial operations and the rule language of the Semantic Web (SWRL). This method is applied in the industrial archaeology domain in order to enhance the knowledge managem…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]semantic webspatial analysisindustrial archaeology[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]ontologyknowledge management[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]SWRL[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]OWL
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