Details

Autor(en) / Beteiligte

• Ehrig, Marc

Titel

Ontology Alignment : Bridging the Semantic Gap [electronic resource]

Auflage

1st ed. 2007

Ort / Verlag

New York, NY : Springer US

Erscheinungsjahr

2007

Beschreibungen/Notizen

• Description based upon print version of record.
• Includes bibliographical references and index.
• Introduction and Overview: Motivation, Contribution, Overview -- Foundations: Ontology, Ontology Alignment, Further Terms, Ontology Similarity, Use Cases, Requirements -- Related Work: Theory of Alignment, Existing Alignment Approaches -- Alignment Process: General Ontology Alignment Process, Alignment Approach, Process for Related Approaches, Evaluation -- Advanced Novel Methods: Efficiency, Machine Learning, Active Alignment, Adaptive Alignment, Integrated Approach -- Tools and Applications: Basic Infrastructure, Ontology Mapping Based on Axioms, Ontology Engineering Platform, Semantic Web and Peer-to-Peer (SWAP), Semantically Enabled Knowledge Technologies (SEKT) -- Next Steps: Generalization, Complex Alignments, Completeness of Alignments, Outlook -- Conclusion: Content Summary, Assessment of Contributions, Final Statements.
• A large number of information systems use many different individual schemas to represent data. Semantically linking these schemas is a necessary precondition to establish interoperability between agents and services. Consequently, ontology alignment and mapping for data integration has become central to building a world-wide semantic web. Ontology Alignment: Bridging the Semantic Gap introduces novel methods and approaches for semantic integration. In addition to developing new methods for ontology alignment, the author provides extensive explanations of up-to-date case studies. The topic of this book, coupled with the application-focused methodology, will appeal to professionals from a number of different domains. Designed for practitioners and researchers in industry, Ontology Alignment: Bridging the Semantic Web Gap is also suitable for advanced-level students in computer science and electrical engineering.
• English