Analyzing the subjective interestingness of association rules

被引：111
作者：
Liu, B [1 ]
Hsu, W [1 ]
Chen, S [1 ]
Ma, YM [1 ]
机构：
[1] Natl Univ Singapore, Sch Comp, Dept Comp Sci, Singapore 117543, Singapore
来源：
IEEE INTELLIGENT SYSTEMS & THEIR APPLICATIONS | 2000年 / 15卷 / 05期
关键词：
We would like to thank many people; especially Minqing Hu; Ken Wong; and Yiyuan Xia; for their contributions to the project. The project is funded by the National Science and Technology Board and National University of Singapore;
D O I：
10.1109/5254.889106
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new approach to help users find interesting rules from a set of discovered association rules is described. This interestingness analysis system (IAS) leverages the user's existing domain knowledge to analyze discovered associations and then rank discovered rules according to various interestingness criteria.
引用
收藏
页码：47 / 55
页数：9
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