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Collaborative Knowledge Management Through Product Lifecycle

A Computational Perspective
BuchKartoniert, Paperback
283 Seiten
Englisch
Springererschienen am03.03.20242023
This book not only presents the state-of-the-art research on knowledge modelling, knowledge retrieval and knowledge reuse, but also elaborates the Collaborative Knowledge Management (CKM) paradigm and the architecture for the next generation of knowledge management systems.mehr
Verfügbare Formate
BuchGebunden
EUR181,89
BuchKartoniert, Paperback
EUR181,89
E-BookPDF1 - PDF WatermarkE-Book
EUR171,19

Produkt

KlappentextThis book not only presents the state-of-the-art research on knowledge modelling, knowledge retrieval and knowledge reuse, but also elaborates the Collaborative Knowledge Management (CKM) paradigm and the architecture for the next generation of knowledge management systems.
Details
ISBN/GTIN978-981-19-9628-3
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2024
Erscheinungsdatum03.03.2024
Auflage2023
Seiten283 Seiten
SpracheEnglisch
Gewicht513 g
IllustrationenXVI, 283 p. 172 illus., 122 illus. in color.
Artikel-Nr.55885116

Inhalt/Kritik

Inhaltsverzeichnis
Knowledge management through product lifecycle.- The collaborative knowledge management paradigm.- Knowledge modelling methods.- Advanced knowledge retrieval methods.- Knowledge reuse in collaborative knowledge management.- Discussion.mehr

Schlagworte

Autor

Dr. Hongwei Wang is a tenured full professor with Zhejiang University and the University of Illinois at Urbana-Champaign Joint Institute where he serves as the vice dean in research and academic lead in intelligent manufacturing. He received the B.S. degree in information technology and instrumentation from Zhejiang University, China, in 2004, the M.S. degree in control science and engineering from Tsinghua University, China, in 2007, and completed the Ph.D. degree in engineering design from the University of Cambridge, in 2010. Prio to joining Zhejiang University, he was a Senior Lecturer in engineering design with the University of Portsmouth, the United Kingdom. His research interests include knowledge engineering, industrial knowledge graph, intelligent and collaborative systems, and data-driven fault diagnosis. His research in these areas has been published in over 120 peer-reviewed papers in well-established journals and international conferences. He has delivered two keynotespeeches and has won four best paper awards in international conferences.



Dr. Gongzhuang Peng is an assistant professor with the Engineering Research Institute, University of Science and Technology Beijing. He received the B.S. degree from School of Automation Science and Electrical Engineering, Beihang University, Beijing, China, in 2012, and the Ph.D. degree from the Department of Automation, Tsinghua University, Beijing, China, in 2018. His research interest concerns knowledge management and smart manufacturing. He has published near 40 peer-reviewed papers in international journals and international conferences, and has won two best paper awards in international conferences.
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