On mining group patterns of mobile users

• Main Authors: WANG, Yida, LIM, Ee Peng, HWANG, San-Yih
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2003
• Subjects: Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/1032; https://ink.library.smu.edu.sg/context/sis_research/article/2031/viewcontent/On_mining_group_patterns_of_mobile_users.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 the spatio-temporal distances among them. Group patterns of users are determined by a distance threshold and a minimum duration. To discover group patterns, we propose the AGP and VG-growth algorithms that are derived from the Apriori and FP-growth algorithms respectively. We further evaluate the efficiencies of these two algorithms using synthetically generated user movement data.