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2011•ASME Press eBooksRequires access

Research of Data Mining Algorithm Based on Association Rules

Changxin Song, Ke Ma

Open publisher page 3 citations

Abstract

Through the research on the existing data mining and association rules algorithms, for the deficiencies of the current association rule mining algorithm Apriori, this paper presents an improved Apriori association rule mining algorithm. The improved algorithm can reduce the number of generated candidate item sets and database scans through cutting of the frequent item set, thus greatly improving the efficiency of mining association rules.

About this research paper

What this paper is about

Through the research on the existing data mining and association rules algorithms, for the deficiencies of the current association rule mining algorithm Apriori, this paper presents an improved Apriori association rule mining algorithm. The improved algorithm can reduce the number of generated candidate item sets and database scans through cutting of the frequent item set, thus greatly improving the efficiency of mining association rules.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

Through the research on the existing data mining and association rules algorithms, for the deficiencies of the current association rule mining algorithm Apriori, this paper presents an improved Apriori association rule mining algorithm. The improved algorithm can reduce the number of generated candidate item sets and database scans through cutting of the frequent item set, thus greatly improving the efficiency of mining association rules.

Key concepts: Association rule learning, Apriori algorithm, Data mining, Computer science, A priori and a posteriori, GSP Algorithm, Association (psychology), Set (abstract data type)

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