Research and Application of Improved Apriori Algorithm
LI Long
LIU Peng
ZHANG Kejia
HUANG Shan
LI Qian
Abstract：Association rules are one of the most important aspects in the field of data mining. Among them,the Apriori algo?rithm is an important part of association rules,the Apriori algorithm is easy to produce in the calculation of two frequent itemsets when a large number of invalid candidate sets,and the problem of redundant scanning of candidate,based on the traditional Apriori algorithm,an improved Apriori algorithm is proposed,namely Apriori-L algorithm. The improved Apriori algorithm can not only im?prove the time efficiency of the calculation of two frequent sets,but also speed up the operation process of the whole algorithm. The Apriori-L algorithm can be used to excavate the stock market module interaction rules,and the linkage stock module can be guessed. The improved algorithm is applied to daily life,and provides the basis for the algorithm to be used. Meanwhile,it verifies the accuracy of the Apriori-L algorithm.
Keywords：association rulesdata miningApriori algorithmtwo frequent sets
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 1293-1297 )