Research on improved Data-Mining Algorithm based on Strong Correlation

被引：0
|
作者：
Hu, Chunhong [1 ]
Wang, Zhengqiang [2 ]
机构：
[1] Yangtze Univ, Coll Comp Sci, Jinzhou 434023, Hubei, Peoples R China
[2] Xiangfan Univ, Dept Phys & Elect Informat Technol, Xiangfan 441053, Peoples R China
来源：
SECOND INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING: WGEC 2008, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/WGEC.2008.119
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The extensive application of association rules in commerce enables itself to be one of the most active research directions in data mining. Recently, the mining of strong correlation item pairs with statistical significance in transaction database receives a certain value. In order to further reduce the cost of testing candidate item pairs in relational database, we have developed the Taper algorithm according to INF property. The developed TaperR algorithm can cut the number of candidate pairs to improve efficiency.
引用
收藏
页码：423 / +
页数：2
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