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

Angermann

 
9783319722085: Taxonomy Matching Using Background Knowledge: Linked Data, Semantic Web and Heterogeneous Repositories

Inhaltsangabe

Part I: Introduction to Taxonomy Matching

Background Taxonomy Matching

Background of Taxonomic Heterogeneity

Part II: Recent Matching Techniques, Algorithms, Systems, Evaluations, and Datasets

Matching Techniques, Algorithms, and Systems

Matching Evaluations and Datasets

Part III: Taxonomy Heterogeneity Applications

Related Areas

Part IV: Conclusions

Conclusions

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Über die Autorin bzw. den Autor

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.

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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 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.

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9783319891576: Taxonomy Matching Using Background Knowledge: Linked Data, Semantic Web and Heterogeneous Repositories

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ISBN 10:  331989157X ISBN 13:  9783319891576
Verlag: Springer, 2019
Softcover