An Efficient Association Rule Mining Algorithm and Business Application

摘要：

In this paper, aim at the inefficient problem of the Apriori algorithms, we design a new matrix data structure, called Co-Occurrence Matrix, in short COM, to store the data information instead of directly using the transactional database. In COM, any item sets can be randomly accessed and counted without many times full scan of the original transactional database. Based on COM, we first divide association rule into two kinds of rule and then we present an efficient algorithms (COM_mining) to find the valid association rules among the frequent items. Finally we apply COM_mining algorithm and Apriori algorithm simultaneously to analyze up-down association relationship between various industry stock blocks of China A stock market. From analytical result we can find that in China A stock market, there are indeed up-down association relationship between various industry stock blocks. At the same time, through comparing COM_mining algorithm and Apriori algorithm in this application, we can see, COM_mining is more efficient than Apriori.

作者: ZHANG Zheng WANG Hui-wen

作者单位: School of Economics and Management Beihang University Beijing, P.R.China

会议类型: 国际会议

会议名称: 2007年通信、电路与系统国际会议(2007 International Conference on Communications,Circuits and Systems Proceedings)

会议地点: 日本福冈

会议语种:英文

在线出版日期: 2007-07-11（万方平台首次上网日期，不代表论文的发表时间）