Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Chang, Furonga; b | Zhang, Bofenga; * | Li, Haiyanb; c | Huang, Mingqinga | Li, Bingchunb | Zhao, Yuea
Affiliations: [a] School of Computer Engineering and Science, Shanghai University, Shanghai, China | [b] School of Computer Science and Technology, Kashi University, Kashi, Xinjiang, China | [c] Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Correspondence: [*] Corresponding author. Bofeng Zhang, School of Computer Engineering and Science, Shanghai University, 200444, Shanghai, China. E-mail: bfzhang@shu.edu.cn.
Abstract: Methods for detecting overlapping communities are essential for understanding complex network structures and extracting implied information. Traditional community detection algorithms have been proven to be unsatisfactory when the network community structure is relatively fuzzy. In this paper, we proposed a novel overlapping community discovery algorithm (ENFI) to address this problem on the micro level using ego-nets. The ENFI approach exploits the micro-characteristics of ego-nets, extracts the ego-net’s local community by calculating the friend intimacy, and then forms the overlapping communities of the network. We conducted experiments on both synthetic and real-world social networks using normalized mutual information (NMI) and overlapping community modularity as evaluation criteria. The results demonstrated that the proposed ENFI algorithm can detect community structures in complex networks more efficiently and accurately than existing state-of-the-art algorithms.
Keywords: Ego-net, overlapping community, friend intimacy, complex network
DOI: 10.3233/JIFS-172242
Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5167-5175, 2019
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl