Mining Short Association Rules from Large Database

被引：0
|
作者：
Ye, Feiyue [1 ]
Chen, Mingxia [1 ]
Qian, Jin [1 ]
机构：
[1] Jiangsu Teachers Univ Technol, Coll Comp Sci & Engn, Changzhou, Peoples R China
来源：
2009 ASIA-PACIFIC CONFERENCE ON INFORMATION PROCESSING (APCIP 2009), VOL 1, PROCEEDINGS | 2009年
关键词：
data mining; association rule; frequent pattern;
D O I：
10.1109/APCIP.2009.98
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Discovering association rules from existing large databases is an important technique. In this paper, we propose an effective algorithm for mining short association rules on large database. It is experimentally demonstrated presented algorithm has an advantage over existing algorithm for mining association rule, it has better performance and flexibility. By verifying the real transaction data from a supermarket, the short for mining association rules is effective too.
引用
收藏
页码：362 / 365
页数：4
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