Mining Mobile Group Patterns: A Trajectory-Based Approach

San-Yih Hwang, Ying-Han Liu, Jeng-Kuen Chiu, Ee-Peng Lim

Abstract: In this paper, we present a group pattern mining approach to derive the grouping information of mobile device users based on a trajectory model. Group patterns of users are determined by distance threshold and minimum time duration. A trajectory model of user movement is adopted to save storage space and to cope with untracked or disconnected location data. To discover group patterns, we propose ATGP algorithm and TVG-growth that are derived from the Apriori and VG-growth algorithms respectively.