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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.
Produkteigenschaften
- Artikelnummer: 9783319978635
- Medium: Buch
- ISBN: 978-3-319-97863-5
- Verlag: Springer International Publishing
- Erscheinungstermin: 08.11.2018
- Sprache(n): Englisch
- Auflage: 1. Auflage 2019
- Serie: Unsupervised and Semi-Supervised Learning
- Produktform: Gebunden
- Gewicht: 471 g
- Seiten: 187
- Format (B x H x T): 160 x 241 x 17 mm
- Ausgabetyp: Kein, Unbekannt