Ontology Alignment
Ehrig, Marc.
Ontology Alignment Bridging the Semantic Gap / [electronic resource] : by Marc Ehrig. - XVIII, 248 p. online resource. - Semantic Web and Beyond, Computing for Human Experience, 4 1559-7474 ; . - Semantic Web and Beyond, Computing for Human Experience, 4 .
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.
9780387365015
10.1007/978-0-387-36501-5 doi
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 Management.
QA76.76.A65
005.7
Ontology Alignment Bridging the Semantic Gap / [electronic resource] : by Marc Ehrig. - XVIII, 248 p. online resource. - Semantic Web and Beyond, Computing for Human Experience, 4 1559-7474 ; . - Semantic Web and Beyond, Computing for Human Experience, 4 .
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.
9780387365015
10.1007/978-0-387-36501-5 doi
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 Management.
QA76.76.A65
005.7