Modeling and Management of Fuzzy Semantic Rdf Data: 1057 - Rilegato

Ma, Zongmin; Li, Guanfeng; Ma, Ruizhe

 
9783031116681: Modeling and Management of Fuzzy Semantic Rdf Data: 1057
Rilegato
ISBN 10: 3031116682 ISBN 13: 9783031116681
Casa editrice: Springer Nature, 2022

Sinossi

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.


Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer Nature
Data di pubblicazione
2022
Lingua
Inglese
ISBN 10 
3031116682
ISBN 13 
9783031116681
Rilegatura
Copertina rigida
Numero edizione
1
Numero di pagine
224
Contatto del produttore
non disponibile
Persona responsabile
CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
Germania

Altre edizioni note dello stesso titolo

9783031116711: Modeling and Management of Fuzzy Semantic RDF Data: 1057

Edizione in evidenza

ISBN 10:  3031116712 ISBN 13:  9783031116711
Casa editrice: Springer, 2023
Brossura