Mining Association Rules Based on Apriori Algorithm and Application

被引:10
|
作者
Wang Pei-ji [1 ]
Shi Lin [1 ]
Bai Jin-niu [2 ]
Zhao Yu-lin [3 ]
机构
[1] Inner Mongolia Univ Sci & Technol, Sch Math Phys & Biol Engn, Baotou 014010, Peoples R China
[2] Inner Mongolia Univ Sci & Technol, Sch Med, Baotou, Peoples R China
[3] Inner Mongdia Branch 2, Baotou, Peoples R China
关键词
apriori algorithm; recognizable matrix; association rules mining; application;
D O I
10.1109/IFCSTA.2009.41
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In the data mining research,mining association rules is an important topic.Apriori algorithm submitted by Agrawal and R.Srikant in 1994 is the most effective algorithm. Aimed at two problems of discovering frequent itemsets in a large database and mining association rules from frequent itemsets, I make some research on mining frequent itemsets algorithm based on apriori algorithm and mining association rules algorithm based on improved measure system.Mining association rules algorithm based on support,confidence and interestingness is improved,aiming at creating interestingness useless rules and losing useful rules. Useless rules are cancelled,creating more reasonable association rules including negative items. The above method is used to mine association rules to the 2002 student score list of computer specialized field in Inner Mongolia university of science and technology.
引用
收藏
页码:141 / +
页数:2
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