期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：5
DOI：10.15680/ijircce.2015.0305027
出版社：S&S Publications
摘要：The effectiveness of mining association rules is a significant field of Knowledge Discovery in Databases(KDD). The Apriori algorithm is a classical algorithm in mining association rules. This paper presents an improvedmethod for Apriori and Frequent Pattern algorithms to increase the efficiency of generating association rules. Thisalgorithm adopts a new method to decrease the redundant generation of sub-itemsets during pruning the candidateitemsets, which can form directly the set of frequent itemset and remove candidates having a subset that is not frequent inthe meantime. This algorithm can raise the probability of obtaining information in scanning database and reduce thepotential scale of itemsets
