Improved Apriori Algorithm for Mining Association Rules

Yu-gang DAI, Xiang ZHANG, Tao XU, Lin YE, Ya-jing MA

Abstract


Apriori algorithm as a classic algorithm in data mining, it has a good performance in a small number of transactions in the database which has been widely used by people, but the algorithm has two inherent flaws, affect the efficiency of Apriori algorithm mining information in large database. Aiming at the Bottleneck Problem Restricting the Efficiency of Apriori Algorithm, in this paper, two inherent flaws of Apriori algorithm are improved, in order to improve Apriori algorithm in large database mining efficiency. The algorithm reduces the number of connections and the number of database scan to shorten the database scan time. Experimental results show, the optimized Apriori algorithm has some improvements in operation efficiency.

Keywords


Apriori algorithm, Association rules, Data mining, Frequent itemsets.Text


DOI
10.12783/dtcse/icmsa2018/23233

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