2005Unpublished venueRequires access

An Effective Method for Generating Association Rules

Gui Xian-cai

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Abstract

Discovering association rules between items in a large database is an important data mining problem as the number of association rule is usually very larger.This paper introduces the concepts of original association rules and proves all rules in the rules set mined by conventional mining algorithms can be generated by the original association rules.Moreover,the number of the original association rules is much less than the number of all rules.Here we give the original association rule algorithm and use an example to show the operational process of the algorithm.

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What this paper is about

Discovering association rules between items in a large database is an important data mining problem as the number of association rule is usually very larger.This paper introduces the concepts of original association rules and proves all rules in the rules set mined by conventional mining algorithms can be generated by the original association rules.Moreover,the number of the original association rules is much less than the number of all rules.Here we give the original association rule algorithm and use an example to show the operational process of the algorithm.

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Available abstract

Discovering association rules between items in a large database is an important data mining problem as the number of association rule is usually very larger.This paper introduces the concepts of original association rules and proves all rules in the rules set mined by conventional mining algorithms can be generated by the original association rules.Moreover,the number of the original association rules is much less than the number of all rules.Here we give the original association rule algorithm and use an example to show the operational process of the algorithm.

Key concepts: Association rule learning, Data mining, Association (psychology), Computer science, Process (computing), Set (abstract data type), Apriori algorithm, Psychology

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