Lecture Notes in Artificial Intelligence Lect.Notes Computer. Tutorial

Association Rule Mining

Models and Algorithms

Authors: Zhang, Chengqi, Zhang, Shichao

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About this Textbook

Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention.
The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.

Table of contents (8 chapters)

Table of contents (8 chapters)
  • Introduction

    Pages 1-23

  • Association Rule

    Pages 25-46

  • Negative Association Rule

    Pages 47-84

  • Causality in Databases

    Pages 85-120

  • Causal Rule Analysis

    Pages 121-159

Buy this book

eBook n/a
  • ISBN 978-3-540-46027-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
Softcover n/a
  • ISBN 978-3-540-43533-4
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Association Rule Mining
Book Subtitle
Models and Algorithms
Authors
Series Title
Lecture Notes in Artificial Intelligence
Series Volume
2307
Copyright
2002
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-46027-5
DOI
10.1007/3-540-46027-6
Softcover ISBN
978-3-540-43533-4
Edition Number
1
Number of Pages
XII, 244
Topics