@inproceedings{0820d93f937241e0b18d22c0a1938dae,
title = "A citation similarity based community detection method in citation networks",
abstract = "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.",
keywords = "citation networks, community detection, paper similarity",
author = "Tianpeng Liu and Kan Li",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2015 ; Conference date: 19-12-2015 Through 20-12-2015",
year = "2016",
month = mar,
day = "7",
doi = "10.1109/IAEAC.2015.7428536",
language = "English",
series = "Proceedings of 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "146--149",
editor = "Bing Xu",
booktitle = "Proceedings of 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2015",
address = "United States",
}
