基于主题的学术社区发现算法

In the field of community identification, the commuinty identification algorithm based on topology can't get good identification result with sparse information in dataset. Aiming to solve the problem, in this paper, we proposed a new academic community identification algorithm based on topic. First, topic model is utilized to extract relationships among authors and build the associated network of authors. Then on the basis of the author's associated network, GN algorithm is used to find the community. As shown in experimental result, the proposed algorithm is effective to solve the problem of loose network structure result from the sparse reference information. And the proposed algorithm also obtains better community identification result, and improves the modularity of community.