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Taxonomy Matching Using Background Knowledge - Heiko Angermann - Naeem Ramzan
Taxonomy Matching Using Background Knowledge - Heiko Angermann - Naeem Ramzan

Taxonomy Matching Using Background Knowledge

Heiko Angermann - Naeem Ramzan
pubblicato da Springer International Publishing

Prezzo online:
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36,39
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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.

Dettagli down

Generi Informatica e Web » Linguaggi e Applicazioni » Database » Scienza dei calcolatori » Comunicazione e reti informatiche , Scienza e Tecnica » Matematica , Economia Diritto e Lavoro » Management » Studi generali

Editore Springer International Publishing

Formato Ebook con Adobe DRM

Pubblicato 08/01/2018

Lingua Inglese

EAN-13 9783319722092

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