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Beschreibung
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.
Techniques, Toolboxes and Applications
Techniques, Toolboxes and Applications
Details
| Verlag | Springer International Publishing |
| Ersterscheinung | 19. Januar 2019 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 312 Gramm |
| Format | Softcover |
| ISBN-13 | 9783030074197 |
| Seiten | 187 |
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