株式会社極東書店トップ > 商品一覧 > Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications. 2019 ed.
商品詳細
Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications. 2019 ed.
・ISBN 978-3-319-97863-5 hard EUR 149.99
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| 著者・編者 | Nasraoui, Olfa / Ben N'Cir, Chiheb-Eddine (eds.), |
|---|---|
| シリーズ | (Unsupervised and Semi-Supervised Learning) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2018 |
| ページ数 | 187 pp. |
| 言語 | ENG |
| ニュース番号 | <A03-185> |
解説
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.