Mining association rule efficiently based on data warehouse

被引：5

作者：

Chen, XH ^{[1
]}

Lai, BC ^{[1
]}

Luo, D ^{[1
]}

机构：

[1] Cent S Univ, Sch Business, Changsha 410083, Peoples R China

来源：

JOURNAL OF CENTRAL SOUTH UNIVERSITY OF TECHNOLOGY | 2003年 / 10卷 / 04期

关键词：

data mining; association rule mining; complete association rule set; least association rule set;

D O I：

10.1007/s11771-003-0042-6

中图分类号：

TF [冶金工业];

学科分类号：

0806 ;

摘要：

The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) it should be the mini mat and the simplest association rule set; 2) its predictive power should in no way be weaker than that of the complete association rule set so that the precision of the association rule set analysis can be guaranteed. By adopting the least association rule set, the pruning of weak rules can be effectively carried out so as to greatly reduce the number of frequent itemset, and therefore improve the mining efficiency. Finally, based on the classical Apriori algorithm, the upward closure property of weak rules is utilized to develop a corresponding efficient algorithm.

引用

页码：375 / 380

页数：6

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