Mining interval sequential patterns

Authors:
Ding-An Chiang;Shao-Lun Lee;Chun-Chi Chen;Ming-Hua Wang
Affiliations:
Department of Information Engineering, Tamkang University, Tan-Shui, Taipei, Taiwan, R.O.C.;Department of Information Management, Oriental Institute of Technology, Pan-Chiao, Taipei, Taiwan, R.O.C.;Department of Information Engineering, Tamkang University, Tan-Shui, Taipei, Taiwan, R.O.C.;Department of Information Management, Nanya Institute of Technology, Jung-Li, Taoyuan, Taiwan, R.O.C.
Venue:
International Journal of Intelligent Systems
Year:
2005

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Abstract

The main task of mining sequential patterns is to analyze the transaction database of a company in order to find out the priorities of items that most customers take when consuming. In this article, we propose a new method—the ISP Algorithm. With this method, we can find out not only the order of consumer items of each customer, but also offer the periodic interval of consumer items of each customer. Compared with other previous periodic association rules, the difference is that the period the algorithm provides is not the repeated purchases in a regular time, but the possible repurchases within a certain time frame. The algorithm utilizes the transaction time interval of individual customers and that of all the customers to find out when and who will buy goods, and what items of goods they will buy. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 359–373, 2005.