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Subspace Clustering on Mobile Data for Discovering Circle of Friends

  • Tao Wu
  • Yujie Fan
  • Zhiling Hong
  • Lifei Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9403)

Abstract

The discovery of circle of friends has risen rapidly in recent years. Traditional methods are mainly based on social network analysis which relies heavily on self-report data, such that these methods have isolated successes with limited accuracy, breadth, and depth. In this paper, we propose a new method which combines clustering technique to automatically discover the circle of friends on mobile data. In our method, the circle of friends is modeled as non-overlapping subspace clusters on mobile data with a Vector Space Model (VSM) based representation, for which a new subspace clustering algorithm is proposed to mine the underlying friend-relationship. The experimental studies on real mobile data demonstrate the effectiveness of the new method, and the results show that our clustering algorithm achieves better performance than the existing clustering algorithms.

Keywords

Circle of friends Mobile data Non-overlapping subspaces Subspace clustering 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Tao Wu
    • 1
    • 2
  • Yujie Fan
    • 1
    • 2
  • Zhiling Hong
    • 3
  • Lifei Chen
    • 1
    • 2
  1. 1.School of Mathematics and Computer ScienceFujian Normal UniversityFuzhouChina
  2. 2.Fujian Provincial Key Laboratory of Network Security and CryptologyFujian Normal UniversityFuzhouChina
  3. 3.Software SchoolXiamen UniversityXiamenChina

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