关键词: 引文网络, 社团划分, 聚类, 文本挖掘, 文本相似度

Abstract:

The study of community discovery has great value to text mining. In order to improve the accuracy of the communities of Citation networks, this paper describes a new community discovering algorithm for literature based on content and topological structure.  First of all, this paper establish the vector space model to calculate the similarity of the adjacent papers, and then refactor the citation network based on the similarity and linking relationship of vertexes. On this basis, we set the similarity of adjacent papers as the weight of the link.The community discovery algorithm is based on the “Louvain community detecting algorithm”. Experiments show that the proposed algorithm is an effective solution to improve the performance of community detection.

Key words: Citation networks, Community discovery, Clustering, Data mining, Text similarity