Ontology Matching - nouveau livre

EAN (ISBN-13): 9783642387210
ISBN (ISBN-10): 3642387217
Date de parution: 2013
Editeur: Springer-Verlag
511 Pages
Langue: eng/Englisch

Livre dans la base de données depuis 2012-08-19T22:44:29+02:00 (Zurich)
Page de détail modifiée en dernier sur 2023-09-28T10:06:14+02:00 (Zurich)
ISBN/EAN: 9783642387210

ISBN - Autres types d'écriture:
3-642-38721-7, 978-3-642-38721-0
Autres types d'écriture et termes associés:
Auteur du livre: jerome, jer, pavel
Titre du livre: ontology, match match

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Données de l'éditeur

Auteur: Jérôme Euzenat; Pavel Shvaiko
Titre: Ontology Matching
Editeur: Springer; Springer Berlin
511 Pages
Date de parution: 2013-11-08
Berlin; Heidelberg; DE
Langue: Anglais
171,19 € (DE)
176,00 € (AT)
201,00 CHF (CH)
Available
XVII, 511 p. 103 illus., 1 illus. in color.

EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Informatik; Informationsrückgewinnung, Information Retrieval; Verstehen; Catalogue Integration; Data Integration; Information Integration; Ontologies; Ontology Alignment; Ontology Engineering; Schema Matching; Semantic Web; C; Information Storage and Retrieval; Computer and Information Systems Applications; Artificial Intelligence; IT in Business; e-Commerce and e-Business; Formal Languages and Automata Theory; Computer Science; Data Warehousing; Angewandte Informatik; Künstliche Intelligenz; Wirtschaftsmathematik und -informatik, IT-Management; Unternehmensanwendungen; Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften; E-Commerce: geschäftliche Aspekte; Theoretische Informatik; BB

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.

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.

, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. Inparticular, 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.

Ontology Matching Ontology Matching

Introduction.- Part I The matching problem.- Applications.- The matching problem.- Methodology.- Part II Ontology matching techniques.- Classifications of ontology matching techniques.- Basic similarity measures.- Global matching methods.- Matching strategies.- Part III Systems and evaluation.- Overview of matching systems.- Evaluation of matching systems.- Part IV Representing, explaining, and processing alignments.- Frameworks and formats: representing alignments.- User involvement.- Processing alignments.- Part V Conclusions.- Conclusions.- Appendix A: Legends of figures.- Appendix B: Running example.- Appendix C: Exercises.- Appendix D: Solution to exercises.

Jérôme Euzenat is senior research scientist at INRIA where he leads the Exmo team dedicated to computer-mediated exchanges of structured knowledge. He is supervising the "Heterogeneity" work package of the Knowledge web network of excellence which aims at structuring the European research community in ontology alignment and merging.

Pavel Shvaiko is a postdoc fellow at the Department of Information and Communication Technology (DIT) of the University of Trento (UniTn), Trento, Italy. In 2006, he finished his PhD on "Iterative Schema-based Semantic Matching". Currently, he works in a European research project on matching multiple schemas, classifications, ontologies as a solution to the semantic heterogeneity problem.

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.

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.

, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. Inparticular, 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.

Ontology Matching Ontology Matching
The most comprehensive state-of-the-art overview of techniques for database schema matching and semantic web applications Summarizes research from the database, information systems, and artificial intelligence communities Combines theoretical foundations with practical application perspectives Second Edition includes a new chapter on methodologies for performing ontology matching, and numerous additions for emerging topics including data interlinking, context-based matching, and user involvement Includes supplementary material: sn.pub/extras