A Citation Similarity Based Community Detection Method in Citation Networks
Citation networks are important for us to understand the academic fields.By resolving the community structure,we can find out the subfields in the network.Many methods have been proposed to detect the communities in networks.However,they are not suitable to use directly in citation networks because they can be misled by some special papers and they do not take full advantage of the information contained in citation networks.To solve the problems,we propose a citation similarity based community detection method to detect the communities in citation networks.By transforming citation network to paper similarity network we can use more information to resolve the community structure in citation networks and identify communities more precisely.The experiment results show that our method performs better in resolving community structure comparing with the method using directly in citation networks.
citation networks community detection paper similarity
Tianpeng Liu Kan Li
Department of Computer Science Beijing Institute of Technology Beijing, China Department of Computer Science Beijing Institute of Technology Beijing China
国际会议
重庆
英文
146-149
2015-12-19（万方平台首次上网日期，不代表论文的发表时间）