Association Rule Mining: Models and Algorithms

✍ Scribed by Chengqi Zhang, Shichao Zhang (eds.)

Publisher: Springer-Verlag Berlin Heidelberg
Year: 2002
Tongue: English
Leaves: 248
Series: Lecture Notes in Computer Science 2307 : Lecture Notes in Artificial Intelligence
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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

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
Association Rules in Very Large Databases....Pages 161-198
Association Rules in Small Databases....Pages 199-224
Conclusion and Future Work....Pages 225-228

✦ Subjects

Artificial Intelligence (incl. Robotics); Database Management; Information Storage and Retrieval; Algorithm Analysis and Problem Complexity

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