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Studies in Big Data

High-Utility Pattern Mining

Theory, Algorithms and Applications

Editors: Fournier-Viger, P., Lin, J.C.-W., Nkambou, R., Vo, B., Tseng, V.S. (Eds.)

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  • Presents an overview of the theory and core methods used in utility mining
  • Covers recent advances in high-utility mining
  • Includes stream, incremental, sequence, and big data mining
  • Discusses important applications and open-source software
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eBook $119.00
price for USA in USD (gross)
  • ISBN 978-3-030-04921-8
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $159.99
price for USA in USD
  • ISBN 978-3-030-04920-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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.

 

Table of contents (12 chapters)

Table of contents (12 chapters)
  • A Survey of High Utility Itemset Mining

    Pages 1-45

    Fournier-Viger, Philippe (et al.)

  • A Comparative Study of Top-K High Utility Itemset Mining Methods

    Pages 47-74

    Krishnamoorthy, Srikumar

  • A Survey of High Utility Pattern Mining Algorithms for Big Data

    Pages 75-96

    Zihayat, Morteza (et al.)

  • A Survey of High Utility Sequential Pattern Mining

    Pages 97-129

    Truong-Chi, Tin (et al.)

  • Efficient Algorithms for High Utility Itemset Mining Without Candidate Generation

    Pages 131-160

    Qu, Jun-Feng (et al.)

Buy this book

eBook $119.00
price for USA in USD (gross)
  • ISBN 978-3-030-04921-8
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $159.99
price for USA in USD
  • ISBN 978-3-030-04920-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
High-Utility Pattern Mining
Book Subtitle
Theory, Algorithms and Applications
Editors
  • Philippe Fournier-Viger
  • Jerry Chun-Wei Lin
  • Roger Nkambou
  • Bay Vo
  • Vincent S. Tseng
Series Title
Studies in Big Data
Series Volume
51
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-04921-8
DOI
10.1007/978-3-030-04921-8
Hardcover ISBN
978-3-030-04920-1
Series ISSN
2197-6503
Edition Number
1
Number of Pages
VIII, 337
Number of Illustrations
44 b/w illustrations, 79 illustrations in colour
Topics