Modeling and Management of Fuzzy Semantic RDF Data (Hardcover, 1st ed. 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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 1057
Release date:	September 2022
First published:	2022
Authors:	Zongmin Ma • Guanfeng Li • Ruizhe Ma
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	210
Edition:	1st ed. 2022
ISBN-13:	978-3-03-111668-1
Categories:	Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-111668-2
Barcode:	9783031116681

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