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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,...

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Bibliographic Details
Main Authors: Zhang, Chengqi, Zhang, Shichao (Author)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2002, 2002
Edition:1st ed. 2002
Series:Lecture Notes in Artificial Intelligence
Subjects:
Information Storage And Retrieval
Artificial Intelligence
Algorithms
Database Management
Information Storage And Retrieval Systems
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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505 0 |a 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 
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653 |a Algorithms 
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520 |a 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 

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