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Taxonomy Matching Using Background Knowledge

Linked Data, Semantic Web and Heterogeneous Repositories

Autor: Heiko Angermann, Naeem Ramzan

Jazyk:

Vazba: Pevná

Vydavatel: Springer International Publishing AG

Dostupnost: Skladem u dodavatele

Odesíláme za 9-15 dnů

966 Kč

This important text/reference presents a comprehensive review of techniques for taxonomy matching, d...

Informace o knize

Autor

Heiko Angermann, Naeem Ramzan

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2018

Stránek

103

EAN

9783319722085

ISBN

3319722085

Enbook ID

18622614

Vydavatel

Springer International Publishing AG

Hmotnost

349

Rozměry

155 x 235 x 12

Kompletní popis

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.

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Taxonomy Matching Using Background Knowledge

Linked Data, Semantic Web and Heterogeneous Repositories

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