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Overlapping community detection combining content and link
- Overlapping community detection combining content and link
- Frontiers of Information Technology & Electronic Engineering Vol. 13, Issue 11, Pages: 828-839(2012)
- Affiliations：
1.Zhejiang Provincial Key Laboratory of Information Network Technology, Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China
2.Department of Computer Science, University of Illinois at Chicago, IL 60607, USA
- Author bio：
Zhong-fei (Mark) ZHANG, E-mail:zhongfei@zju.edu.cn
- Funds：
DOI：10.1631/jzus.C1200049
CLC： TP391Received：05 March 2012，
Revised：2012-10-12，
Published：2012-11
- Accepted：
Scan QR Code
Zhou-zhou HE, Zhong-fei(Mark) ZHANG, Philip S. YU. Overlapping community detection combining content and link[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(11): 828-839.
Zhou-zhou HE, Zhong-fei(Mark) ZHANG, Philip S. YU. Overlapping community detection combining content and link[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(11): 828-839. DOI： 10.1631/jzus.C1200049.
摘要
Abstract
In classic community detection
it is assumed that communities are exclusive
in the sense of either soft clustering or hard clustering. It has come to attention in the recent literature that many real-world problems violate this assumption
and thus overlapping community detection has become a hot research topic. The existing work on this topic uses either content or link information
but not both of them. In this paper
we deal with the issue of overlapping community detection by combining content and link information. We develop an effective solution called subgraph overlapping clustering (SOC) and evaluate this new approach in comparison with several peer methods in the literature that use either content or link information. The evaluations demonstrate the effectiveness and promise of SOC in dealing with large scale real datasets.
关键词
Keywords
references
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