2005Microcomputer DevelopmentRequires access

Original Association Rules and Its Application

Gui Xian-cai, H. Peng

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Abstract

Discovering association rules between items in a large database is an important data mining problem.The number of association rules is usually very large.So introduces the concepts of simple association rules and the original association rules,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 analyzes tow association rules,and gives the original association rules algorithm and an example shows 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.The number of association rules is usually very large.So introduces the concepts of simple association rules and the original association rules,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 analyzes tow association rules,and gives the original association rules algorithm and an example shows 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.The number of association rules is usually very large.So introduces the concepts of simple association rules and the original association rules,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 analyzes tow association rules,and gives the original association rules algorithm and an example shows the operational process of the algorithm.

Key concepts: Association rule learning, Computer science, Association (psychology), Data mining, Set (abstract data type), Process (computing), Simple (philosophy), Programming language

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