An Algorithm of Association Rules Mining Based on Restricted Conditional Probability Distribution

摘要：

There are excessive and disordered rules generated by traditional approaches of association rule mining, many of which are redundant, so that they are difficult for users to understand and make use of. Agrawal et al pointed out the bottleneck of transaction number increase association rules according to the index increase. To solve this problem, a new method was represented, which is based on restricted conditional probability distribution to get a condensed rules set by removing redundant rules. Our set of rules is more meaningful, more concise and users are interested in than others. Especially, the number of rules in rules-set has been reduced greatly. We find that it is an effective method of association rules mining from examples, finally poses future research.

关键词： Data Mining Association Rules Restricted Conditional Probability Distribution

作者: Wenliang Cao Xuanzi Hu Fasheng Liu

作者单位: Department of Computer Engineering DongGuan Polytechnic Dongguan, Guangdong, China Faculty of Information Engineering Jiangxi University of Science and Technology Ganzhou, Jiangxi, Ch

会议类型: 国际会议

会议名称: Third International Symposium on Information Science and Engineering(第三届信息科学与工程国际会议 ISISE 2010)

会议地点: 上海

会议语种:英文

页码: 517-520

在线出版日期: 2010-12-24（万方平台首次上网日期，不代表论文的发表时间）