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portada Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications
Type
Physical Book
Publisher
Author
Language
English
Pages
187
Format
Hardcover
Dimensions
23.4x15.6x1.3 cm
Weight
0.46 kg.
ISBN13
9783319978635
Categories

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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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.

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