Overview
- First state-of-the-art overview of techniques applicable to database schema matching and semantic web applications
- Summarizes research from database, information systems, and artificial intelligence communities
- Uniquely combines theoretical foundations with practical application perspectives
- Includes supplementary material: sn.pub/extras
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About this book
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.
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Table of contents (12 chapters)
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Front Matter
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Introduction
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The matching problem
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Front Matter
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Ontology matching techniques
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Front Matter
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Systems and evaluation
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Front Matter
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Representing, explaining, and processing alignments
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Front Matter
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Conclusions
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Back Matter
Authors and Affiliations
About the authors
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.
Bibliographic Information
Book Title: Ontology Matching
Authors: Jérôme Euzenat, Pavel Shvaiko
DOI: https://doi.org/10.1007/978-3-540-49612-0
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2007
eBook ISBN: 978-3-540-49612-0Published: 15 June 2007
Edition Number: 1
Number of Pages: IX, 333
Topics: Programming Techniques, Information Storage and Retrieval, Information Systems Applications (incl. Internet), Artificial Intelligence, IT in Business, e-Commerce/e-business