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Ontology matching

Author: Jérôme Euzenat
Publisher: Berlin ; New York : Springer, ©2007.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Euzenat, Jérôme.
Ontology matching.
Berlin ; New York : Springer, ©2007
(DLC) 2007926257
(OCoLC)124038270
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Jérôme Euzenat
ISBN: 9783540496120 3540496122 3540496114 9783540496113 1280937572 9781280937576
OCLC Number: 185026967
Description: 1 online resource (ix, 333 pages) : illustrations
Contents: Cover --
Contents --
Introduction --
Part I: The matching problem --
CH. 1 Applications --
1.1 Ontology engineering --
1.2 Information integration --
1.3 Peer-to-peer information sharing --
1.4 Web service composition --
1.5 Autonomous communication systems --
1.6 Navigation and query answering on the web --
1.7 Summary --
CH. 2 The matching problem --
2.1 Vocabularies, schemas and ontologies --
2.2 Ontology language --
2.3 Types of heterogeneity --
2.4 Terminology --
2.5 The ontology matching problem --
2.6 Summary --
Part II: Ontology matching techniques --
CH. 3 Classifications of ontology matching techniques --
3.1 Matching dimensions --
3.2 Classification of matching approaches --
3.3 Other classifications --
3.4 Summary --
CH. 4 Basic techniques --
4.1 Similarity, distances and other measures --
4.2 Name-based techniques --
4.3 Structure-based techniques --
4.4 Extensional techniques --
4.5 Semantic-based techniques --
4.6 Summary --
CH. 5 Matching strategies --
5.1 Matcher composition --
5.2 Similarity aggregation --
5.3 Global similarity computation --
5.4 Learning methods --
5.5 Probabilistic methods --
5.6 User involvement and dynamic composition --
5.7 Alignment extraction --
5.8 Summary --
Part III: Systems and evaluation --
CH. 6 Overview of matching systems --
6.1 Schema-based systems --
6.2 Instance-based systems --
6.3 Mixed, schema-based and instance-based systems --
6.4 Meta-matching systems --
6.5 Summary --
CH. 7 Evaluation of matching systems --
7.1 Evaluation principles --
7.2 Data sets for evaluation --
7.3 Evaluation measures --
7.4 Application-specific evaluation --
7.5 Summary --
Part IV: Representing, explaining, and processing alignments --
CH. 8 Frameworks and formats: representing alignments --
8.1 Alignment formats --
8.2 Alignment frameworks --
8.3 Ontology editors with alignment manipulation capabilities --
8.4 Summary --
CH. 9 Explaining alignments --
9.1 Justifications --
9.2 Explanation approaches --
9.3 A default explanation --
9.4 Explaining basic matchers --
9.5 Explaining the matching process --
9.6 Arguing about correspondences --
9.7 Summary --
CH. 10 Processing alignments --
10.1 Ontology merging --
10.2 Ontology transformation --
10.3 Data translation --
10.4 Mediation --
10.5 Reasoning --
10.6 Towards an alignment service --
10.7 Summary --
Part V: Conclusions --
CH. 11 Conclusions --
11.1 A brief outlook of the trends in the field --
11.2 Future challenges --
11.3 Final words --
Appendix A: Legends of figures --
Appendix B: Running example --
Appendix C: Exercises --
References --
IDX. Index --
Last Page.
Responsibility: Jérôme Euzenat, Pavel Shvaiko.
More information:

Abstract:

Ontologies are viewed as the silver bullet for many applications, but in open or evolving systems, different parties can adopt different ontologies. This increases heterogeneity problems rather than  Read more...

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