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Ontology Alignment [electronic resource] :Bridging the Semantic Gap / by Marc Ehrig.

by Ehrig, Marc [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Semantic Web and Beyond, Computing for Human Experience: 4Publisher: Boston, MA : Springer US, 2007.Description: XVII, 247 p. online resource.ISBN: 9780387365015.Subject(s): Computer science | Information systems | Database management | Multimedia systems | Artificial intelligence | Electronic commerce | Computer Science | Information Systems Applications (incl.Internet) | Artificial Intelligence (incl. Robotics) | Information Systems and Communication Service | Multimedia Information Systems | Electronic Commerce/e-business | Database ManagementDDC classification: 005.7 Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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.
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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.

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