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Modeling and Management of Fuzzy Semantic RDF Data / by Zongmin Ma, Guanfeng Li, Ruizhe Ma

By: Ma, Zongmin, autor
Contributor(s): Li, Guanfeng, autor | Ma, Ruizhe, autor
Series: (Studies in Computational Intelligence, 1860-9503; 1057).Publisher: Cham : Springer International Publishing, 2022Edition: 1st edition 2022.Description: 1 recurso en línea (XI, 210 páginas) : 41 ilustraciones, 6 ilustraciones a color.ISBN: 9783031116698.Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
RDF Data and Management -- Fuzzy Sets and Fuzzy Database Modeling -- Fuzzy RDF Modeling -- Persistence of Fuzzy RDF and Fuzzy RDF Schema -- Fuzzy RDF Queries.
Summary: This book systemically presents the latest research findings in fuzzy RDF data modeling and management. Fuzziness widely exist in many data and knowledge intensive applications. With the increasing amount of metadata available, efficient and scalable management of massive semantic data with uncertainty is of crucial importance. This book goes to great depth concerning the fast-growing topic of technologies and approaches of modeling and managing fuzzy metadata with Resource Description Framework (RDF) format. Its major topics include representation of fuzzy RDF data, fuzzy RDF graph matching, query of fuzzy RDF data, and persistence of fuzzy RDF data in diverse databases. The objective of the book is to provide the state-of-the-art information to researchers, practitioners, and postgraduates students who work on the area of big data intelligence and at the same time serve as the uncertain data and knowledge engineering professional as a valuable real-world reference.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Acceso electrónico eBook.25122204
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RDF Data and Management -- Fuzzy Sets and Fuzzy Database Modeling -- Fuzzy RDF Modeling -- Persistence of Fuzzy RDF and Fuzzy RDF Schema -- Fuzzy RDF Queries.

This book systemically presents the latest research findings in fuzzy RDF data modeling and management. Fuzziness widely exist in many data and knowledge intensive applications. With the increasing amount of metadata available, efficient and scalable management of massive semantic data with uncertainty is of crucial importance. This book goes to great depth concerning the fast-growing topic of technologies and approaches of modeling and managing fuzzy metadata with Resource Description Framework (RDF) format. Its major topics include representation of fuzzy RDF data, fuzzy RDF graph matching, query of fuzzy RDF data, and persistence of fuzzy RDF data in diverse databases. The objective of the book is to provide the state-of-the-art information to researchers, practitioners, and postgraduates students who work on the area of big data intelligence and at the same time serve as the uncertain data and knowledge engineering professional as a valuable real-world reference.

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