Mining Association Rules Based on Apriori Algorithm and Application

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.

关键词： apriori algorithm recognizable matrix association rules mining application

作者: WANG Pei-ji SHI Lin BAI Jin-niu ZHAO Yu-lin

作者单位: School of mathematics,physics and biological engineering, Inner Mongolia University of Science and T School of medicine, Inner Mongolia University of Science and Technology, Baotou 014010, China Branch 2,Inner Mongdia No. 1 Machinery,Baotou 014010, China

会议类型: 国际会议

会议名称: 2009 International Forum on Computer Science-Technology and Applications(2009年国际计算机科学技术与应用论坛 IFCSTA 2009)

会议地点: 重庆

会议语种:英文

页码: 141-143

在线出版日期: 2009-12-25（万方平台首次上网日期，不代表论文的发表时间）