Overlapping Community Discovery Algorithm Based on Hierarchical Agglomerative Clustering

摘要

Overlapping community is a response to the real network structure in social networks and in real society in order to solve the problems such as the parameters of the existing overlapping community discovery algorithm being too large, excessive overlap and no guarantee of stability of multiple runs. In this paper, the method of calculating the node degree of membership was proposed, and an overlapping community discovery algorithm based on the local optimal expansion cohesion idea was designed. Firstly, the initial core community was constructed with the highest importance node and its neighbor nodes. Secondly, the core community was extended by node attribution degree until the termination condition of the algorithm was satisfied. Finally, the experimental results were compared with the existing algorithms. The experiments show that the result of the division by the improved algorithm has been significantly improved compared to the other algorithms, and the community structure after the division is more reasonable.