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Clustering Methods for Big Data Analytics

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Clustering Methods for Big Data Analytics Synopsis

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.

About This Edition

ISBN: 9783030074197
Publication date:
Author: Olfa Nasraoui
Publisher: Springer Nature Switzerland AG
Format: Paperback
Pagination: 187 pages
Series: Unsupervised and Semi-Supervised Learning
Genres: Communications engineering / telecommunications
Artificial intelligence
Data mining
Expert systems / knowledge-based systems
Databases
Pattern recognition

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