Subspace Clustering on Mobile Data for Discovering Circle of Friends

• Published in: Knowledge Science, Engineering and Management pp. 703 - 711
• Main Authors: Wu, Tao, Fan, Yujie, Hong, Zhiling, Chen, Lifei
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing 2015
• Series: Lecture Notes in Computer Science
• Subjects: Circle of friends; Mobile data; Non-overlapping subspaces; Subspace clustering
• ISBN: 9783319251585; 3319251589
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-25159-2_64

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.