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Book 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.

Book details

Book category Books in English Computing & information technology Computer science Artificial intelligence

• Full title: Clustering Methods for Big Data Analytics
• Subtitle: Techniques, Toolboxes and Applications
• Author: Olfa Nasraoui, Chiheb-Eddine Ben N'Cir
• Language: English
• Binding: Hardback
• Number of pages: 187
• EAN: 9783319978635
• ISBN: 3319978632
• ID: 19762441
• Publisher: Springer International Publishing AG
• Weight: 471 g
• Dimensions: 235 × 155 × 15 mm
• Date of publishing: 08. November 2018

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