A Fast Algorithm for Mining Association Rules

被引：0
|
作者：
黄刘生
陈华平
王洵
陈国良
机构：
来源：
Journal of Computer Science & Technology | 2000年 / 06期
关键词：
database; data mining; large itemset; association rule; minimum support; minimum confidence;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, the problem of discovering association rules between items in a large database of sales transactions is discussed, and a novel algorithm, BitMatrix, is proposed. The proposed algorithm is fundamentally different from the known algorithms Apriori and AprioriTid. Empirical evaluation shows that the algorithm outperforms the known ones for large databases. Scale-up experiments show that the algorithm scales linearly with the number of transactions.
引用
收藏
页码：619 / 624
页数：6
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