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English | PDF,EPUB | 2018 (2019 Edition) | 192 Pages | ISBN : 3319978632 | 20.22 MB​

Clustering Methods for Big Data Analytics (Olfa Nasraoui, Chiheb-Eddine Ben N'Cir) (2019)
Catergory: Computer Technology, Technology, Engineering, Nonfiction
Publisher: Springer International Publishing

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.

Contents of Download:
3319978632.epub (Olfa Nasraoui, Chiheb-Eddine Ben N'Cir) (2019) (13.88 MB)
3319978632.pdf (Olfa Nasraoui) (2018) (6.34 MB)

️ Clustering Methods For Big Data Analytics Techniques Toolboxes And Applications (20.22 MB)
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RapidGator Link(s)

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