Abstract
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.
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References
Forsyth, D.R.: Group Dynamics. Wadsworth, Belmont (1999)
Guralnik, V., Srivastava, J.: Event Detection from Time Series Data. In: Proceedings of ACM International Conference on Knowledge Discovery and Data Mining (KDD 2000) (2000)
Liu, Y.-H.: Mining Mobile Group Patterns: A Trajectory-based Approach. master thesis, Department of Information Management, National Sun Yat-sen U., Available at, http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0730104-102312
Mokhtar, H., Su, J., Ibarra, O.H.: On moving object queries. In: Proceedings of the ACM Symposium on Principles of Database Systems (PODS) (2002)
Park, H.K., Son, J.H., Kim, M.-H.: An Efficient Spatiotemporal Indexing Method for Moving Objects in Mobile Communication Environments. In: Chen, M.-S., Chrysanthis, P.K., Sloman, M., Zaslavsky, A. (eds.) MDM 2003. LNCS, vol. 2574, pp. 78–91. Springer, Heidelberg (2003)
Saltenis, S., Jensen, C.S., Leutenegger, S.T., Lopez, M.A.: Indexing the positions of continuously moving objects. In: Proc. of 2000 ACM SIGMOD Conference (2000)
Shekhar, S., Chawla, S.: Introduction to Spatial Data Mining. In: Spatial Databases: A Tour, ch.7. Prentice Hall, New Jersey (2003)
Vazirgiannis, M., Wolfson, O.: A spatiotemporal model and language for moving objects on road networks. In: Proc. of Symposium on Spatial and Temporal Databases (SSTD) (2001)
Wang, Y., Lim, E.-P., Hwang, S.-Y.: On Mining Group Patterns of Mobile Users. In: Proc. Of the 14th International Conference on Database and Expert Systems Application (DEXA 2003) (2003)
Wang, Y., Lim, E.-P., Hwang, S.-Y.: Effective Group Pattern Mining Using Data Summarization. In: Lee, Y., Li, J., Whang, K.-Y., Lee, D. (eds.) DASFAA 2004. LNCS, vol. 2973, pp. 895–907. Springer, Heidelberg (2004)
Wolfson, O., Sistla, A.P., Chamberlain, S., Yesha, Y.: Updating and querying databases that track mobile units. Distributed and Parallel Databases (1999)
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Hwang, SY., Liu, YH., Chiu, JK., Lim, EP. (2005). Mining Mobile Group Patterns: A Trajectory-Based Approach. In: Ho, T.B., Cheung, D., Liu, H. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2005. Lecture Notes in Computer Science(), vol 3518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11430919_82
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DOI: https://doi.org/10.1007/11430919_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26076-9
Online ISBN: 978-3-540-31935-1
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