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Inferring Social Groups Using Call Logs

  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2008 Workshops (OTM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5333))

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Abstract

Recent increase in population of mobile phone users makes it a valuable source of information for social network analysis. For a given call log, how much can we tell about the person’s social group? Unnoticeably, phone user’s calling personality and habit has been concealed in the call logs from which we believe that it can be extracted to infer its user’s social group information. In this paper, we present an end-to-end system for inferring social networks based on “only” call logs using kernel-based naïve Bayesian learning. We also introduce normalized mutual information for feature selection process. Our model is evaluated with real-life call logs where it performs at high accuracy rate of 81.82%.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, USA

    Santi Phithakkitnukoon & Ram Dantu

Authors
  1. Santi Phithakkitnukoon
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  2. Ram Dantu
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Editor information

Editors and Affiliations

  1. STARLab, Vrije Universiteit Brussel (VUB),, Bldg G/10, Pleinlaan 2, 1050, Brussels, Belgium

    Robert Meersman

  2. School of Computer Science and Information Technology, RMIT University, Bld 10.10, 376-392 Swanston Street, VIC 3001, Melbourne, Australia

    Zahir Tari

  3. Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, Boadilla del Monte, 28660, Madrid, Spain

    Pilar Herrero

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© 2008 Springer-Verlag Berlin Heidelberg

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Phithakkitnukoon, S., Dantu, R. (2008). Inferring Social Groups Using Call Logs. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2008 Workshops. OTM 2008. Lecture Notes in Computer Science, vol 5333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88875-8_40

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  • DOI: https://doi.org/10.1007/978-3-540-88875-8_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88874-1

  • Online ISBN: 978-3-540-88875-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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