A Link Prediction Method That Can Learn from Network Dynamics

Link prediction is an important issue in Social Network Analysis area. Most of the existing link prediction methods aim to find the missing links or to predict the future links mainly based on a static network, ignoring the evolution of the network over time. This paper proposes a link prediction method that can learn from network dynamics. Using machine learning techniques, the method models the changes over time of several structural features in the network. One classifier is trained for each structural feature and the final prediction result is obtained by weighting all the classifiers. The experimental results of three real collaboration networks show that the proposed method outperforms both a traditional static method and a state-of-art dynamic method. Moreover, the experiments also show that the ability to describe network dynamics for different structural features is also different.

[1]  Jennifer Neville,et al.  Exploiting time-varying relationships in statistical relational models , 2007, WebKDD/SNA-KDD '07.

[2]  Leo Katz,et al.  A new status index derived from sociometric analysis , 1953 .

[3]  Ricardo B. C. Prudêncio,et al.  Time Series Based Link Prediction , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

[4]  Wei Tang,et al.  Supervised Link Prediction Using Multiple Sources , 2010, 2010 IEEE International Conference on Data Mining.

[5]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .

[6]  Srikanta J. Bedathur,et al.  Towards time-aware link prediction in evolving social networks , 2009, SNA-KDD '09.

[7]  Tao Zhou,et al.  Link prediction in weighted networks: The role of weak ties , 2010 .

[8]  M. Newman.  Clustering and preferential attachment in growing networks. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  Lada A. Adamic,et al.  Friends and neighbors on the Web , 2003, Soc. Networks.

[10]  Isaac Olusegun Osunmakinde,et al.  Temporality in Link Prediction: Understanding Social Complexity , 2009 .

[11]  Zan Huang,et al.  The Time-Series Link Prediction Problem with Applications in Communication Surveillance , 2009, INFORMS J. Comput..

[12]  Ben Taskar,et al.  Link Prediction in Relational Data , 2003, NIPS.

[13]  Jon M. Kleinberg,et al.  The link-prediction problem for social networks , 2007, J. Assoc. Inf. Sci. Technol..

[14]  Ravi Kumar,et al.  Structure and evolution of online social networks , 2006, KDD '06.

[15]  A. Barabasi,et al.  Evolution of the social network of scientific collaborations , 2001, cond-mat/0104162.

[16]  Purnamrita Sarkar,et al.  Nonparametric Link Prediction in Dynamic Networks , 2012, ICML.