Multi-dimensional semantic clustering of large databases for association rule mining

被引：2

作者：

Ananthanarayana, VS ^{[1
]}

Murty, MN ^{[1
]}

Subramanian, DK ^{[1
]}

机构：

[1] Indian Inst Sci, Dept Comp Sci & Automat, Bangalore 560012, Karnataka, India

来源：

PATTERN RECOGNITION | 2001年 / 34卷 / 04期

关键词：

Computational complexity - Computational linguistics - Computer simulation - Data mining - Data structures - Database systems;

D O I：

10.1016/S0031-3203(00)00128-X

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we showed efficient ways of mining intra-transaction association rules based on semantic knowledge. We presented a scheme for generating abstract association rules based on cluster descriptions. This may be viewed as inter-transaction association rule mining activity. The proposed scheme is used to successfully mine meaningful association rules from simulated data. © 2001 Elsevier Science B.V.

引用

页码：939 / 941

页数：3