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Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications
Nasraoui, Olfa ; Ben N'cir, Chiheb-Eddine (Author)
·
Springer
· Hardcover
Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications - Nasraoui, Olfa ; Ben n'Cir, Chiheb-Eddine
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Origin: U.S.A.
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Synopsis "Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications"
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.
