Taxonomy Matching Using Background Knowledge
Language: English
Published by Springer International Publishing, 2018
- Hardcover
- New
Seller: moluna, Greven, Germanymoluna
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Add to basketItem description from seller
Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides in-depth coverage of the state of the art in taxonomy matching, and the related fields of ontology matching and schema matching Reviews matching strategies, matching algorithms, matching systems and OAEI campaigns, in addition to alterna.
Seller Inventory # 179443051
- Title
- Taxonomy Matching Using Background Knowledge
- Author
- Heiko Angermann|Naeem Ramzan
- Publisher
- Springer International Publishing
- Publication year
- 2018
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319722085
- ISBN 13
- 9783319722085
- Seller catalogs
- Mathematik/Naturwissenschaften/Technik/Medizin
This important text/reference presents a comprehensive review of techniques for taxonomy matching, discussing matching algorithms, analyzing matching systems, and comparing matching evaluation approaches. Different methods are investigated in accordance with the criteria of the Ontology Alignment Evaluation Initiative (OAEI). The text also highlights promising developments and innovative guidelines, to further motivate researchers and practitioners in the field.
Topics and features: discusses the fundamentals and the latest developments in taxonomy matching, including the related fields of ontology matching and schema matching; reviews next-generation matching strategies, matching algorithms, matching systems, and OAEI campaigns, as well as alternative evaluations; examines how the latest techniques make use of different sources of background knowledge to enable precise matching between repositories; describes the theoretical background, state-of-the-art research, and practical real-world applications; covers the fields of dynamic taxonomies, personalized directories, catalog segmentation, and recommender systems.This stimulating book is an essential reference for practitioners engaged in data science and business intelligence, and for researchers specializing in taxonomy matching and semantic similarity assessment. The work is also suitable as a supplementary text for advanced undergraduate and postgraduate courses on information and metadata management.
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Heiko Angermann is an e-commerce, enterprise content management, and omni/multi-channel consultant, and the Head of Project Management at an e-commerce consulting house located in Nuremberg, Germany.
Prof. Naeem Ramzan is a full Professor of Computing Engineering in the School of Engineering and Computing at the University of West of Scotland, Paisley, UK. His other publications include the successful Springer title Social Media Retrieval.
"About the title" may belong to another edition of this title.
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