Clustering Methods for Big Data Analytics: Techniques, Toolboxes and Applications (Unsupervised and Semi-Supervised Learning)

  • 出版商: Springer
  • 出版日期: 2018-11-08
  • 售價: $6,100
  • 貴賓價: 9.5$5,795
  • 語言: 英文
  • 頁數: 187
  • 裝訂: Hardcover
  • ISBN: 3319978632
  • ISBN-13: 9783319978635
  • 相關分類: 大數據 Big-dataData Science
  • 海外代購書籍(需單獨結帳)
    無現貨庫存(No stock available)

商品描述

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.