Exploiting game theoretic analysis for link recommendation in social networks
Refereed conference paper presented and published in conference proceedings


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AbstractThe popularity of Online Social Networks (OSNs) has attracted great research interests in different fields. In Economics, researchers use game theory to analyze the mechanism of network formation, which is called Network Formation Game. While in Computer Science, much effort has been done in building machine learning models to predict future or missing links. However, there are few works considering how to combine game theoretic analysis and machine learning models. Therefore, in this paper, we study the problem of Exploiting Game Theoretic Analysis for Link Recommendation in Social Networks. Our goal is to improve link recommendation accuracy via leveraging the power of Network Formation Games into machine learning models. We present two different approaches to solve this problem. First, we propose a three-phase method that straightforwardly combines game theoretic analysis with machine learning models. Second, we develop a unified model, BPRLGT, that incorporates Network Formation Game into a Bayesian ranking framework for link recommendation. Specifically, BPRLGT takes advantage of network topology and we design a game theoretic sampling approach to improve its training process. The experiments are conducted on four real world datasets and the results on all datasets demonstrate that both our proposed three-phase method and the unified ranking model outperform the baseline methods.
All Author(s) ListZhao T., Zhao H.V., King I.
Name of Conference24th ACM International Conference on Information and Knowledge Management, CIKM 2015
Start Date of Conference19/10/2015
End Date of Conference23/10/2015
Place of ConferenceMelbourne
Country/Region of ConferenceAustralia
Detailed descriptionorganized by ACM,\n\nTo ORKTS: http://people.eng.unimelb.edu.au/ammoffat/cikm15-accepted.pdf
Year2015
Month10
Day17
Volume Number19-23-Oct-2015
Pages851 - 860
ISBN9781450337946
LanguagesEnglish-United Kingdom
KeywordsGame theory, Link prediction, Network formation game

Last updated on 2020-09-08 at 04:17