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High-Utility Pattern Mining

Theory, Algorithms and Applications

  • Philippe Fournier-Viger
  • Jerry Chun-Wei Lin
  • Roger Nkambou
  • Bay Vo
  • Vincent S. Tseng

Part of the Studies in Big Data book series (SBD, volume 51)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Philippe Fournier-Viger, Jerry Chun-Wei Lin, Tin Truong-Chi, Roger Nkambou
    Pages 1-45
  3. Morteza Zihayat, Mehdi Kargar, Jaroslaw Szlichta
    Pages 75-96
  4. Tin Truong-Chi, Philippe Fournier-Viger
    Pages 97-129
  5. Jun-Feng Qu, Mengchi Liu, Philippe Fournier-Viger
    Pages 131-160
  6. Loan T. T. Nguyen, Thang Mai, Bay Vo
    Pages 161-174
  7. Supachai Laoviboon, Komate Amphawan
    Pages 175-205
  8. Duy-Tai Dinh, Van-Nam Huynh, Bac Le, Philippe Fournier-Viger, Ut Huynh, Quang-Minh Nguyen
    Pages 207-232
  9. Youcef Djenouri, Philippe Fournier-Viger, Asma Belhadi, Jerry Chun-Wei Lin
    Pages 261-278
  10. Cheng-Wei Wu, Philippe Fournier-Viger, Jia-Yuan Gu, Vincent S. Tseng
    Pages 279-302
  11. Wolfgang Jentner, Daniel A. Keim
    Pages 303-337

About this book

Introduction

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.

 

Keywords

High Utility Pattern Mining Pattern Mining Big Data Data Mining High Utility Mining

Editors and affiliations

  • Philippe Fournier-Viger
    • 1
  • Jerry Chun-Wei Lin
    • 2
  • Roger Nkambou
    • 3
  • Bay Vo
    • 4
  • Vincent S. Tseng
    • 5
  1. 1.Harbin Institute of Technology (Shenzhen)ShenzhenChina
  2. 2.Western Norway University of Applied SciencesBergenNorway
  3. 3.Université du Québec à MontréalMontrealCanada
  4. 4.Ho Chi Minh City University of TechnologyHo Chi Minh CityVietnam
  5. 5.National Chiao Tung UniversityHsinchuTaiwan

Bibliographic information

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