Abstract
Link prediction in social networks such as collaboration networks and friendship networks have recently attracted a great deal of attention. There have been numerous attempts to address this problem through diverse approaches. In the present paper, we focus on the temporal behavior of the link strength, particularly the relationship between the time stamps of interactions or links and the temporal behavior of link strength and how link strength affects future link evolution. Most of the previous studies neglected the impact of time stamps of the interactions and of the links on link evolution. The gap between the current time and the time stamps of the interactions or links is also important to link evolution. In the present paper, we introduced a new time aware index, referred to as time score, that captures the important aspects of time stamps of interactions and the temporality of the link strengths. We apply time score to two social network data sets, namely, a coauthorship network data set and a Facebook friendship network data set. The results reveal a significant improvement in predicting future links.
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References
Adamic, L.A., Adar, E.: Friends and neighbors on the web. Social Networks 25, 211–230 (2003)
Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: Smote: Synthetic minority over-sampling technique. Journal of Artificial Intelligence Research 16, 321–357 (2002)
Cortes, C., Vapnik, V.: Support-vector networks. Machine Learning 20, 273–297 (1995)
Getoor, L.: Link mining: a new data mining challenge. SIGKDD Explor. 5(1), 84–89 (2003)
Getoor, L., Diehl, C.P.: Link mining: a survey. SIGKDD Explor. 7(2), 3–12 (2005)
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The weka data mining software: an update. SIGKDD Explor. Newsl. 11(1), 10–18 (2009)
Hasan, M.A., Chaoji, V., Salem, S., Zaki, M.: Link prediction using supervised learning. In: Proceedings of SDM 2006 Workshop on Link Analysis, Counterterrorism and Security (2006)
Leroy, V., Cambazoglu, B.B., Bonchi, F.: Cold start link prediction. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 393–402 (2010)
Liben-Nowell, D., Kleinberg, J.: The link prediction problem for social networks. In: Proceedings of the 12th International Conference on Information and Knowledge Management, pp. 556–559 (2003)
Lichtenwalter, R.N., Lussier, J.T., Chawla, N.V.: New perspectives and methods in link prediction. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 243–252 (2010)
Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008)
Newman, M.E.J.: Clustering and preferential attachment in growing networks. Phys. Rev. E 64(2), 025102 (2001)
Pavlov, M., Ichise, R.: Finding experts by link prediction in co-authorship networks. In: Proceedings of the Workshop on Finding Experts on the Web with Semantics (November 2007)
Quinlan, J.R.: C4.5: programs for machine learning (1993)
Sachan, M., Ichise, R.: Using abstract information and community alignment information for link prediction. In: Proceedings of 2nd International Conference on Machine Learning and Computing (ICMLC), pp. 61–65 (2010)
Tylenda, T., Angelova, R., Bedathur, S.: Towards time-aware link prediction in evolving social networks. In: Proceedings of the 3rd Workshop on Social Network Mining and Analysis, pp. 1–10 (2009)
Viswanath, B., Mislove, A., Cha, M., Gummadi, K.P.: On the Evolution of User Interaction in Facebook. In: Proceedings of the 2nd ACM SIGCOMM Workshop on Social Networks (August 2009)
Wang, C., Satuluri, V., Parthasarathy, S.: Local probabilistic models for link prediction. In: Proceedings of the 7th IEEE International Conference on Data Mining, pp. 322–331 (2007)
Wohlfarth, T., Ichise, R.: Semantic and event-based approach for link prediction. In: Yamaguchi, T. (ed.) PAKM 2008. LNCS (LNAI), vol. 5345, pp. 50–61. Springer, Heidelberg (2008)
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Munasinghe, L., Ichise, R. (2011). Time Aware Index for Link Prediction in Social Networks. In: Cuzzocrea, A., Dayal, U. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2011. Lecture Notes in Computer Science, vol 6862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23544-3_26
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DOI: https://doi.org/10.1007/978-3-642-23544-3_26
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