Mining interval sequential patterns

✍ Scribed by Ding-An Chiang; Shao-Lun Lee; Chun-Chi Chen; Ming-Hua Wang

• Book ID: 102279909
• Publisher: John Wiley and Sons
• Year: 2005
• Tongue: English
• Weight: 272 KB
• Volume: 20
• Category: Article
• ISSN: 0884-8173
• DOI: 10.1002/int.20070

✦ Synopsis

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.