Reinforcement Label Propagation Algorithm Based on History Record
With the continuous development of Internet, social networks are becoming more and more complex, and the research on these complex networks has attracted many researchers’ attention. A large number of community discovery algorithms have emerged, among which the label propagation algorithm is widely used because of its simplicity and efficiency. However, this algorithm has poor stability due to the randomness in the label propagation process. To solve the problem, we propose a reinforcement label propagation algorithm (RLPA) in this paper. In RLPA, a similarity matrix is generated from the historical records of classification, which can be adopted to obtain the final result of community detection. The experimental results show that our algorithm can not only get better performance in accuracy, but also has higher stability.
KeywordsData mining Community discovery Label propagation algorithm
This work is supported by National High-tech R&D Program of China (863 Program) under Grants 2015AA01A301, 2015AA010901, and 2015AA01A301, by program for New Century Excellent Talents in University by National Science Foundation (NSF) China 61272142, 61402492, 61402486, 61379146, 61272483, by the open project of State Key Laboratory of High-end Server & Storage Technology (2014HSSA01).
- 3.Leung, I.X., Hui, P., Li, P., Crowcroft, J.: Towards real-time community detection in large networks. Phys. Rev. E: Stat. Nonlinear Soft Matter Phys. 79(6 Pt 2), 066107 (2008)Google Scholar
- 11.Adamic, L.A., Glance, N.: The political blogosphere and the 2004 US election: divided they blog. In: Proceedings of the 3rd international workshop on Link discovery, pp. 36–43. ACM (2005)Google Scholar