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  2007, Vol. 20 Issue (5): 661-666    DOI:
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An Algorithm for Mining Maximum Frequent Itemsets
LI QingFen1,2, WANG Li1, ZHOU WeiLin1,2, CHEN HuoWang2
1.Department of Computer and Electronic Engineering, Hunan Business College,
Changsha 410205
2.School of Computer Science, National University of Defense Technology,
Changsha 410073

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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 FPTREE 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 subproject, minimal support minimal combination in repeat array, is proposed in the course of studying MSMCA.
Key wordsAssociation Rules      Maximum Frequent Itemsets      Minimal Support Minimal Combination Algorithm (MSMCA)      Minimal Support Minimal Combination in Repeat Array (MSMCRA)     
Received: 20 June 2006     
ZTFLH: TP311.131  
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LI QingFen
WANG Li
ZHOU WeiLin
CHEN HuoWang
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LI QingFen,WANG Li,ZHOU WeiLin等. An Algorithm for Mining Maximum Frequent Itemsets[J]. , 2007, 20(5): 661-666.
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http://manu46.magtech.com.cn/Jweb_prai/EN/      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2007/V20/I5/661
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