Overview

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.  

Full Product Details

Author:   Marc Ehrig
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2007 ed.
Volume:   4
Dimensions:   Width: 15.50cm , Height: 1.50cm , Length: 23.50cm
Weight:   1.220kg
ISBN:  

9780387328058

ISBN 10:   038732805
Pages:   248
Publication Date:   12 October 2006
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of 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.

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