Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications Softcover Repri Edition Contributor(s): Nasraoui, Olfa (Editor), Ben n'Cir, Chiheb-Eddine (Editor) |
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ISBN: 3030074196 ISBN-13: 9783030074197 Publisher: Springer OUR PRICE: $161.49 Product Type: Paperback - Other Formats Published: January 2019 |
Additional Information |
BISAC Categories: - Technology & Engineering | Telecommunications - Computers | Databases - Data Mining - Business & Economics | Industries - Computers & Information Technology |
Dewey: 006.3 |
Series: Unsupervised and Semi-Supervised Learning |
Physical Information: 0.42" H x 6.14" W x 9.21" (0.63 lbs) 187 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. |