Clustering Methods for Big Data Analytics : Techniques, Toolboxes and Applications Paperback / softback
Edited by Olfa Nasraoui, Chiheb-Eddine Ben n'Cir
Part of the Unsupervised and Semi-Supervised Learning series
Paperback / softback
Description
This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems.
The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks.
The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.
Information
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Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:187 pages, 31 Illustrations, color; 32 Illustrations, black and white; IX, 187 p. 63 illus., 31 illu
- Publisher:Springer Nature Switzerland AG
- Publication Date:19/01/2019
- Category:
- ISBN:9783030074197
Information
-
Available to Order - This title is available to order, with delivery expected within 2 weeks
- Format:Paperback / softback
- Pages:187 pages, 31 Illustrations, color; 32 Illustrations, black and white; IX, 187 p. 63 illus., 31 illu
- Publisher:Springer Nature Switzerland AG
- Publication Date:19/01/2019
- Category:
- ISBN:9783030074197
