Abstract
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. © Springer-Verlag Berlin Heidelberg 2003.
Cite
CITATION STYLE
Wang, Y., Lim, E. P., & Hwang, S. Y. (2003). On mining group patterns of mobile users. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2736, 287–296. https://doi.org/10.1007/978-3-540-45227-0_29
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