2007Harbin Ligong Daxue xuebaoRequires access

Improvement of Apriori Algorithm

Zhao Song, Liquan Sun

Open publisher page 3 citations

Abstract

Apriori algorithm is the most classical algorithm of all the association rules mining methods,but Apriori algorithm has two faults.Firstly,this algorithm has to scan transaction database many times.Secondly,this algorithm has to produce many candidate itemsets.IThis paper puts forward a new algorithm,this algorithm scans transaction database only one time through adding Tid_list to candidate itemsets C_1,and can reduce the number of candidate itemsets on basis of the character of frequent itemsets,so as to improve the efficiency of Apriori algo- rithm.

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What this paper is about

Apriori algorithm is the most classical algorithm of all the association rules mining methods,but Apriori algorithm has two faults.Firstly,this algorithm has to scan transaction database many times.Secondly,this algorithm has to produce many candidate itemsets.IThis paper puts forward a new algorithm,this algorithm scans transaction database only one time through adding Tid_list to candidate itemsets C_1,and can reduce the number of candidate itemsets on basis of the character of frequent itemsets,so as to improve the efficiency of Apriori algo- rithm.

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

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Available abstract

Apriori algorithm is the most classical algorithm of all the association rules mining methods,but Apriori algorithm has two faults.Firstly,this algorithm has to scan transaction database many times.Secondly,this algorithm has to produce many candidate itemsets.IThis paper puts forward a new algorithm,this algorithm scans transaction database only one time through adding Tid_list to candidate itemsets C_1,and can reduce the number of candidate itemsets on basis of the character of frequent itemsets,so as to improve the efficiency of Apriori algo- rithm.

Key concepts: Apriori algorithm, Association rule learning, Data mining, Database transaction, GSP Algorithm, A priori and a posteriori, Computer science, Algorithm

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