Mining sequential mobile access patterns efficiently in mobile web systems

The rapid advance of wireless and web technologies enable the mobile web applications to provide plenty kinds of services for mobile users. Under a mobile Web system, analyzing mobile user's movement sequences and requested services is important for wide applications in wireless communication like data allocation, data replication, location-based and personalization services. The main challenge in this research issue is to effectively deal with the user's diverse behavior and the huge amount of data. However, to our best knowledge, no studies have been done on the problem of mining sequential mobile access patterns with both movement and service requests considered simultaneously. In this paper, we propose a novel data mining method, namely SMAP-Mine, that can discover patterns of sequential movement associated with requested services for mobile users in mobile web systems. Through empirical evaluation on various simulation conditions, the proposed method is shown to deliver excellent performance in terms of accuracy, execution efficiency, and scalability.