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Mining Frequency Pattern from Mobile Users

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3215))

Abstract

Group pattern was introduced to find groups of mobile users associated by means of physical distance and amount of time spent together. This paper addresses the inherent problem of group pattern, that mobile user are often not physically close together when they use mobile technology, by proposing frequency pattern. Frequency pattern use creative method to calculate frequency of communication between mobile users. By using frequency rather than physical distance, the closeness of two mobile users can better be represented. Performance of the proposed method indicates a suitable segment size and alpha value needs to be selected to get the best result.

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References

  1. Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules. In: Proc. 20th Int. Conf. Very Large Data Bases (1994)

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  2. Lim, E.-P., et al.: In Search Of Knowledge About Mobile Users (2003)

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  3. Ng, R.T., Han, J.: Efficient and Effective Clustering Methods for Spatial Data Mining. In: 20th International Conference on Very Large Data Bases, Santiago, Chile proceedings, September 12–15 (1994)

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  4. Wang, Y., Lim, E.-P., Hwang, S.-Y.: On Mining Group Patterns of Mobile Users. In: Mařík, V., Štěpánková, O., Retschitzegger, W. (eds.) DEXA 2003. LNCS, vol. 2736, pp. 287–296. Springer, Heidelberg (2003)

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© 2004 Springer-Verlag Berlin Heidelberg

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Goh, J., Taniar, D. (2004). Mining Frequency Pattern from Mobile Users. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30134-9_106

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  • DOI: https://doi.org/10.1007/978-3-540-30134-9_106

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23205-6

  • Online ISBN: 978-3-540-30134-9

  • eBook Packages: Springer Book Archive

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