Association rule mining is an important data mining areas of research contents, frequent itemset mining association rules mining is one of the key issues. According to the existing frequent itemset mining algorithm, based on the existing problems , this paper put forward the Apriori algorithm analysis system for Apriori-frequent itemset mining algorithm. The algorithm used overlap strategy to reduce scanning databases, thereby algorithm achieved higher efficiency. Experimental results show that the efficiency of algorithm is 1 ~ 4 times than Apriori system.%关联规则挖掘是数据挖掘领域中重要的研究内容,频繁项集挖掘又是关联规则挖掘中的关键问题之一.针对已有的频繁项集挖掘算法存在的问题,通过对Apriori算法的分析,提出了Inter-Apriori频繁项集挖掘算法.该算法使用交集策略减少扫描数据库的次数,从而使算法达到较高的效率.实验结果表明,Inter-Apriori算法是Apfiofi算法效率的2～4倍.
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