Abstract
In this paper, by exploiting the log of call detail records, we present a solution procedure of mining user moving patterns in a mobile computing system. Specifically, we propose algorithm LS to accurately determine similar moving sequences from the log of call detail records so as to obtain moving behaviors of users. By exploring the feature of spatial-temporal locality, we develop algorithm TC to group call detail records into clusters. In light of the concept of regression, we devise algorithm MF to derive moving functions of moving behaviors. Performance of the proposed solution procedure is analyzed and sensitivity analysis on several design parameters is conducted. It is shown by our simulation results that user moving patterns obtained by our solution procedure are of very high quality and in fact very close to real user moving behaviors.
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© 2005 Springer-Verlag Berlin Heidelberg
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Hung, CC., Peng, WC., Huang, JL. (2005). Exploring Regression for Mining User Moving Patterns in a Mobile Computing System. In: Yang, L.T., Rana, O.F., Di Martino, B., Dongarra, J. (eds) High Performance Computing and Communications. HPCC 2005. Lecture Notes in Computer Science, vol 3726. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11557654_98
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DOI: https://doi.org/10.1007/11557654_98
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29031-5
Online ISBN: 978-3-540-32079-1
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