Reinforcement Label Propagation Algorithm Based on History Record

摘要

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.