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High-Utility Pattern Mining

Theory, Algorithms and Applications
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Description

This book presents an overview of techniques for discovering high-utility patterns (patterns with a high importance) in data. It introduces the main types of high-utility patterns, as well as the theory and core algorithms for high-utility pattern mining, and describes recent advances, applications, open-source software, and research opportunities. It also discusses several types of discrete data, including customer transaction data and sequential data. The book consists of twelve chapters, seven of which are surveys presenting the main subfields of high-utility pattern mining, including itemset mining, sequential pattern mining, big data pattern mining, metaheuristic-based approaches, privacy-preserving pattern mining, and pattern visualization. The remaining five chapters describe key techniques and applications, such as discovering concise representations and regular patterns.  
Release date Australia
January 31st, 2019
Contributors
  • Edited by Bay Vo
  • Edited by Jerry Chun-Wei Lin
  • Edited by Philippe Fournier-Viger
  • Edited by Roger Nkambou
  • Edited by Vincent S. Tseng
Pages
337
Edition
1st ed. 2019
Audience
  • Professional & Vocational
Illustrations
79 Illustrations, color; 44 Illustrations, black and white; VIII, 337 p. 123 illus., 79 illus. in color.
ISBN-13
9783030049201
Product ID
28575203

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