Clustering Methods for Big Data Analytics
Techniques, Toolboxes and Applications
Olfa Nasraoui editor Chiheb-Eddine Ben N'Cir editor
Format:Paperback
Publisher:Springer Nature Switzerland AG
Published:19th Jan '19
Currently unavailable, and unfortunately no date known when it will be back
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.
ISBN: 9783030074197
Dimensions: unknown
Weight: unknown
187 pages
Softcover reprint of the original 1st ed. 2019