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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.
Content Level »Research
Keywords »Bridging - Data Integration - Gap - Information Systems - Internet - Language - Machine Learning - Ontology Alignment - Peer - Peer-to-peer - Semantic - Semantic Web
and Overview.- and Overview.- Foundations.- Definitions.- Scenarios.- Related Work.- Ontology Alignment Approach.- Process.- Advanced Methods.- Implementation and Application.- Tools.- Semantic Web and Peer-to-Peer — SWAP.- Semantically Enabled Knowledge Technologies — SEKT.- Towards Next Generation Semantic Alignment.- Next Steps.- Future.- Conclusion.