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.
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Wang, Y., Lim, EP., Hwang, SY. (2003). On Mining Group Patterns of Mobile Users. In: MaÅ™Ãk, V., Retschitzegger, W., Å tÄ›pánková, O. (eds) Database and Expert Systems Applications. DEXA 2003. Lecture Notes in Computer Science, vol 2736. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45227-0_29
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DOI: https://doi.org/10.1007/978-3-540-45227-0_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40806-2
Online ISBN: 978-3-540-45227-0
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