Association Rule Mining Models and Algorithms /

• Main Authors: Zhang, Chengqi (Author, http://id.loc.gov/vocabulary/relators/aut), Zhang, Shichao (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2002.
• Edition: 1st ed. 2002.
• Series: Lecture Notes in Artificial Intelligence ; 2307
• Subjects: Artificial intelligence.; Database management.; Information storage and retrieval.; Algorithms.; Artificial Intelligence.; Database Management.; Information Storage and Retrieval.; Algorithm Analysis and Problem Complexity.
• Physical Description: XII, 244 p. online resource.
• ISBN: 9783540460275
• DOI: 10.1007/3-540-46027-6

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.