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Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications (Unsupervised and Semi-Supervised Learning) by Olfa Nasraoui, Chiheb-Eddine Ben N'Cir is a nonfiction available to read on EtoBox.

What is Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications (Unsupervised and Semi-Supervised Learning) about?

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. . Read more... Abstract: 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. Read more...

Who reads Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications (Unsupervised and Semi-Supervised Learning)?

Author

Olfa Nasraoui, Chiheb-Eddine Ben N'Cir

Publisher

Springer International Publishing

Published

2019

Language

EN

ISBN

9783319978642

Category

nonfiction

Subjects

Computer Science, Mathematics, Engineering