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Taxonomy Matching Using Background Knowledge : Linked Data, Semantic Web and Heterogeneous Repositories

Author: Heiko Angermann; Naeem Ramzan
Publisher: Cham : Springer International Publishing, 2017
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Additional Physical Format: Erscheint auch als:
Druck-Ausgabe
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Heiko Angermann; Naeem Ramzan
ISBN: 9783319722092 3319722093
OCLC Number: 1021379077
Description: 1 Online-Ressource (XIV, 103 Seiten 14 Illustrationen)
Responsibility: by Heiko Angermann, Naeem Ramzan.

Abstract:

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. Dr. Heiko Angermannis 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 Ramzanis 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.

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