Association Rule Mining - Models and Algorithms

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.

List of contents

Association Rule.- Negative Association Rule.- Causality in Databases.- Causal Rule Analysis.- Association Rules in Very Large Databases.- Association Rules in Small Databases.- Conclusion and Future Work.

Summary

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.

Product details

• Authors: Chengq Zhang, Chengqi Zhang, Shichao Zhang
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 27.05.2002
• EAN: 9783540435334
• ISBN: 978-3-540-43533-4
• No. of pages: 244
• Weight: 400 g
• Illustrations: XII, 244 p.
• Series: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; B, Algorithmen und Datenstrukturen, machine learning, Algorithms, Datenbanken, Artificial Intelligence, Data Warehousing, Informationsrückgewinnung, Information Retrieval, computer science, Information Retrieval, Learning, Database Management, database programming, Algorithms & data structures, Algorithm Analysis and Problem Complexity, Information Storage and Retrieval, Databases, knowledge discovery