A General Model for Sequential Pattern Mining with a Progressive Database

Although there have been many recent studies on the mining of sequential patterns in a static database and in a database with increasing data, these works, in general, do not fully explore the effect of deleting old data from the sequences in the database. When sequential patterns are generated, the newly arriving patterns may not be identified as frequent sequential patterns due to the existence of old data and sequences. Even worse, the obsolete sequential patterns that are not frequent recently may stay in the reported results. In practice, users are usually more interested in the recent data than the old ones. To capture the dynamic nature of data addition and deletion, we propose a general model of sequential pattern mining with a progressive database while the data in the database may be static, inserted, or deleted. In addition, we present a progressive algorithm Pisa, which stands for Progressive mIning of Sequential pAtterns, to progressively discover sequential patterns in de...

• Type: Journal
• Year: 2008
• Where: TKDE
• Authors: Jen-Wei Huang, Chi-Yao Tseng, Jian Chih Ou, Ming-Syan Chen
• Keywords: Database, Sequential Pattern, Static Database, TKDE 2008