Mining mobile group patterns: A trajectory-based approach

• Main Authors: HWANG, San-Yih, LIU, Ying-Han, CHIU, Jeng-Kuen, LIM, Ee Peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2005
• Subjects: Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/1034; https://ink.library.smu.edu.sg/context/sis_research/article/2033/viewcontent/Hwang2005_Chapter_MiningMobileGroupPatternsATraj.pdf
• Institution: Singapore Management University

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.