LI QingFen1,2, WANG Li1, ZHOU WeiLin1,2, CHEN HuoWang2
1.Department of Computer and Electronic Engineering, Hunan Business College, Changsha 410205 2.School of Computer Science, National University of Defense Technology, Changsha 410073
Abstract：Mining complete set of frequent patterns remains a key problem to the application of association rules. Up to date, the most commonly used methods are Apriori algorithm and FPTREE algorithm.In this paper, a high efficient algorithm, minimal support minimal combination algorithm (MSMCA), is proposed. It is completely different from the two existing methods. The candidate set of frequent itemsets are not produced by using MSMCA, thus the cost of computer reduces largely. In addition, a subproject, minimal support minimal combination in repeat array, is proposed in the course of studying MSMCA.
李清峰，王莉，周伟林，陈火旺. 一种挖掘最大频繁集的算法*[J]. 模式识别与人工智能, 2007, 20(5): 661-666.
LI QingFen , WANG Li , ZHOU WeiLin , CHEN HuoWang. An Algorithm for Mining Maximum Frequent Itemsets. , 2007, 20(5): 661-666.
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2007, Vol. 20 
