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Clustering Methods for Big Data Analytics

Techniques, Toolboxes and Applications

By: Olfa Nasraoui (Editor), Chiheb-Eddine Ben N'Cir (Editor)

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Paperback | 19 January 2019

At a Glance

Paperback
200 Pages

Dimensions(cm)
23.39 x 15.6 x 1.07

Paperback

$373.75

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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.

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