On Progressive Sequential Pattern Mining

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. 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. In addition, we present a progressive concept to progressively discover sequential patterns in recent time period of interest.