Frequent Pattern Mining

  • Charu C. Aggarwal
  • Jiawei Han

Table of contents

  1. Front Matter
    Pages i-xix
  2. Charu C. Aggarwal
    Pages 1-17
  3. Charu C. Aggarwal, Mansurul A. Bhuiyan, Mohammad Al Hasan
    Pages 19-64
  4. Jiawei Han, Jian Pei
    Pages 65-81
  5. Feida Zhu
    Pages 83-104
  6. Jilles Vreeken, Nikolaj Tatti
    Pages 105-134
  7. Luiza Antonie, Jundong Li, Osmar Zaiane
    Pages 135-145
  8. Siegfried Nijssen, Albrecht Zimmermann
    Pages 147-163
  9. Matthijs van Leeuwen, Jilles Vreeken
    Pages 165-198
  10. Victor E. Lee, Ruoming Jin, Gagan Agrawal
    Pages 199-224
  11. David C. Anastasiu, Jeremy Iverson, Shaden Smith, George Karypis
    Pages 225-259
  12. Wei Shen, Jianyong Wang, Jiawei Han
    Pages 261-282
  13. Hong Cheng, Xifeng Yan, Jiawei Han
    Pages 307-338
  14. Carson Kai-Sang Leung
    Pages 339-367
  15. Aris Gkoulalas-Divanis, Jayant Haritsa, Murat Kantarcioglu
    Pages 369-401
  16. Arthur Zimek, Ira Assent, Jilles Vreeken
    Pages 403-423
  17. Albrecht Zimmermann, Siegfried Nijssen
    Pages 425-442
  18. Charu C. Aggarwal
    Pages 443-467
  19. Back Matter
    Pages 469-471

About this book

Introduction

This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.

Keywords

Association rules Biometrics Data classification Data mining Data stream pattern mining Data streams Frequent pattern mining Frequent patterns Large itemsets Numerical data Pattern recognition Privacy preserving methods Sequential pattern mining Sequential patterns Vertical data representation

Editors and affiliations

  • Charu C. Aggarwal
    • 1
  • Jiawei Han
    • 2
  1. 1.IBMYorktown HeightsUSA
  2. 2.University of Illinois at Urbana-ChampaignUrbanaUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-07821-2
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-07820-5
  • Online ISBN 978-3-319-07821-2
  • About this book