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Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaiko’s book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, artificial intelligence. With Ontology Matching, researchers and practitioners will find a reference book which presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can equally be applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a detailed account of matching techniques and matching systems in a systematic way from theoretical, practical and application perspectives.
Ontologies (Information retrieval) --- Semantic integration (Computer systems) --- Ontologies (Recherche de l'information) --- Intégration sémantique (Systèmes informatiques) --- Ontologies (Information retrieval). --- Semantic integration (Computer systems). --- Engineering & Applied Sciences --- Electrical & Computer Engineering --- Telecommunications --- Computer Science --- Intégration sémantique (Systèmes informatiques) --- EPUB-LIV-FT LIVINFOR SPRINGER-B --- Integration, Semantic (Computer systems) --- Computer science. --- Information technology. --- Business --- Computer programming. --- Information storage and retrieval. --- Artificial intelligence. --- E-commerce. --- Computer Science. --- Programming Techniques. --- Information Storage and Retrieval. --- Information Systems Applications (incl. Internet). --- Artificial Intelligence (incl. Robotics). --- IT in Business. --- e-Commerce/e-business. --- Data processing. --- Data structures (Computer science) --- Integrated software --- Semantic computing --- Information storage and retrieva. --- Artificial Intelligence. --- IT (Information technology) --- Technology --- Telematics --- Information superhighway --- Knowledge management --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Informatics --- Science --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Application software. --- Business—Data processing. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Cybercommerce --- E-business --- E-commerce --- E-tailing --- eBusiness --- eCommerce --- Electronic business --- Internet commerce --- Internet retailing --- Online commerce --- Web retailing --- Commerce --- Programming
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Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaiko’s book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, and artificial intelligence. The second edition of Ontology Matching has been thoroughly revised and updated to reflect the most recent advances in this quickly developing area, which resulted in more than 150 pages of new content. In particular, the book includes a new chapter dedicated to the methodology for performing ontology matching. It also covers emerging topics, such as data interlinking, ontology partitioning and pruning, context-based matching, matcher tuning, alignment debugging, and user involvement in matching, to mention a few. More than 100 state-of-the-art matching systems and frameworks were reviewed. With Ontology Matching, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can be equally applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a systematic and detailed account of matching techniques and matching systems from theoretical, practical and application perspectives.
Computer Science --- Information storage and retrieval systems --- Artificial intelligence --- Management information systems --- Ontologies (Information retrieval) --- Semantic integration (Computer systems) --- Integration, Semantic (Computer systems) --- Integrated software --- Semantic computing --- Data structures (Computer science) --- Information storage and retrieval systems. --- Artificial intelligence. --- Information technology. --- Computer science. --- Information Storage and Retrieval. --- Information Systems Applications (incl. Internet). --- Artificial Intelligence. --- IT in Business. --- e-Commerce/e-business. --- Mathematical Logic and Formal Languages. --- IT (Information technology) --- Technology --- Telematics --- Information superhighway --- Knowledge management --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Informatics --- Science --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Information storage and retrieval. --- Application software. --- Business—Data processing. --- E-commerce. --- Mathematical logic. --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Cybercommerce --- E-business --- E-commerce --- E-tailing --- eBusiness --- eCommerce --- Electronic business --- Internet commerce --- Internet retailing --- Online commerce --- Web retailing --- Commerce --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software
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Metaphysics --- Mathematical logic --- Distribution strategy --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- ICT (informatie- en communicatietechnieken) --- IR (information retrieval) --- ontologie --- bedrijfseconomie --- informatiesystemen --- e-commerce --- wiskunde --- informatica management --- logica --- robots
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Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaiko’s book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, and artificial intelligence. The second edition of Ontology Matching has been thoroughly revised and updated to reflect the most recent advances in this quickly developing area, which resulted in more than 150 pages of new content. In particular, the book includes a new chapter dedicated to the methodology for performing ontology matching. It also covers emerging topics, such as data interlinking, ontology partitioning and pruning, context-based matching, matcher tuning, alignment debugging, and user involvement in matching, to mention a few. More than 100 state-of-the-art matching systems and frameworks were reviewed. With Ontology Matching, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can be equally applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a systematic and detailed account of matching techniques and matching systems from theoretical, practical and application perspectives.
Information retrieval --- Mathematical logic --- Applied marketing --- Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- IR (information retrieval) --- bedrijfseconomie --- e-business --- computers --- informatiesystemen --- e-commerce --- wiskunde --- KI (kunstmatige intelligentie) --- informatica management --- logica --- computerkunde --- robots
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Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- ICT (informatie- en communicatietechnieken) --- IR (information retrieval) --- informatiesystemen --- software engineering --- computernetwerken --- robots
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The 12th Conference on Arti?cial Intelligence: Methodology, Systems, Appli- tions(AIMSA2006)washeldinVarnaontheBlackSeacoastduringSeptember, 12-15,2006.The AIMSA conferenceserieshas provideda biennial forum for the presentation of arti?cial intelligence research and development since 1984. The conference, which is held in Bulgaria, covers the full range of topics in arti?cial intelligence and related disciplines and provides an ideal forum for international scienti?c exchange between Central/Eastern Europe and the rest of the world. The 2006 edition perpetuates this tradition. For AIMSA 2006, we wanted to place special emphasis on a speci?c phen- enon that a?ects all areas of arti?cial intelligence: the application and leverage of arti?cial intelligence technology in the context of human collaboration which today is mediated by the Web. Arti?cial intelligence is used to support human communicationinawidevarietyofways.Forexample,reasoningovertheSem- tic Web, analyzing relationships between people, enhancing the user experience by learning from their behavior, applying natural language to large multilingual corpora, planning a combination of Web services, and adapting and person- izing educational material. A plethora of arti?cial intelligence techniques are amenable to facilitating communication on the Web. Moreover,these techniques are not deployed in isolation but are typically combined with results from other disciplines suchasthe socialsciences,discretemathematics,networkcomputing, or cryptography. However, as its name indicates the conference is also dedicated to arti?cial intelligence in its entirety. As such, AIMSA remains a generalist arti?cial intel- genceconferencewithtracksonconstraintsatisfaction,agents,ontology,decision support, natural language processing and machine learning. The Web e?ect has not created its own new sub-discipline of arti?cial intelligence but rather a?ects all of its sub-areas.
Mathematical statistics --- Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- ICT (informatie- en communicatietechnieken) --- IR (information retrieval) --- factoranalyse --- informatica --- informatiesystemen --- KI (kunstmatige intelligentie) --- robots
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Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaiko's book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, artificial intelligence. With Ontology Matching, researchers and practitioners will find a reference book which presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can equally be applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a detailed account of matching techniques and matching systems in a systematic way from theoretical, practical and application perspectives.
Metaphysics --- Mathematical logic --- Distribution strategy --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- ICT (informatie- en communicatietechnieken) --- IR (information retrieval) --- ontologie --- bedrijfseconomie --- informatiesystemen --- e-commerce --- wiskunde --- informatica management --- logica --- robots
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Mathematical statistics --- Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- ICT (informatie- en communicatietechnieken) --- IR (information retrieval) --- factoranalyse --- informatica --- informatiesystemen --- KI (kunstmatige intelligentie) --- robots
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This book constitutes the refereed proceedings of the 16th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2008, held in Acitrezza, Sicily, Italy, in September/October 2008. The 17 revised full papers and 15 revised short papers presented together with 3 invited talks were carefully reviewed and selected from 102 submissions. The papers are organized in topical sections on knowledge patterns and knowledge representation, matching ontologies and data integration, natural language, knowledge acquisition and annotations, search, query and interaction, as well as ontologies.
Knowledge acquisition (Expert systems) --- Semantic Web --- Information Technology --- Artificial Intelligence --- Artificial intelligence. --- Computer Communication Networks. --- Database management. --- Information storage and retrieva. --- Information systems. --- Artificial Intelligence. --- Database Management. --- Information Systems Applications (incl. Internet). --- Information Storage and Retrieval. --- Computer Appl. in Administrative Data Processing. --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Computer communication systems. --- Application software. --- Information storage and retrieval. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Distributed processing
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This volume contains the papers presented at the 2nd European Semantic Web Conference (ESWC 2005) held in Heraklion, Crete, Greece, from 29th May to 1st June, 2005. The vision of the Semantic Web is to enhance today's Web via the exploi- tion of machine-processable metadata. The explicit representation of the sem- tics of data, accompanied with domain theories (ontologies), will enable a web that provides a qualitatively new level of service. It will weave together an - crediblylargenetworkofhumanknowledgeandwillcomplementitwithmachine processability. Various automated services will help the user to achieve goals by accessing and providing information in a machine-understandable form. This process may ultimately create extremely knowledgeable systems with various specialized reasoning services systems. Many technologies and methodologies are being developed within arti?cial intelligence, human language technology, machine learning, databases, software engineering and information systems that can contribute to the realization of this vision. The 2nd Annual European Semantic Web Conference presented the latest results in research and applications of Semantic Web technologies. Following the success of the ?rst edition, ESWC showed a signi?cant increase in participation. With148submissions,thenumberofpapersdoubledthatofthepreviousedition. Each submission was evaluated by at least three reviewers. The selection process resulted in the acceptance of 48 papers for publication and presentation at the conference (an acceptance rate of 32%). Papers did not come only from Europe but also from other continents.
Computer science. --- Database management. --- Application software. --- Computer communication systems. --- Software engineering. --- Computer Science, general. --- Popular Computer Science. --- Database Management. --- Information Systems Applications (incl. Internet). --- Computer Communication Networks. --- Software Engineering.
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