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Modeling and Management of Fuzzy Semantic RDF Data (Studies in Computational Intelligence, nr. 1057)

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en Limba Engleză Hardback – 09 Sep 2022
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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Specificații

ISBN-13: 9783031116681
ISBN-10: 3031116682
Ilustrații: XI, 210 p. 41 illus., 6 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.51 kg
Ediția: 1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării: Cham, Switzerland

Cuprins

RDF Data and Management.- Fuzzy Sets and Fuzzy Database Modeling.- Fuzzy RDF Modeling.- Persistence of Fuzzy RDF and Fuzzy RDF Schema.- Fuzzy RDF Queries.

Textul de pe ultima copertă

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.

Caracteristici

Applies fuzzy logic to represent and process uncertain semantic data with the Resource Description Framework (RDF)
Presents recent advances in fuzzy RDF data modeling and management
Explicitly describes the modeling and dealing with uncertainty in semantic data