Semi-Supervised Community Detection is a community detection paradigm that, as a subcategory of graph clustering methods, incorporates partial prior knowledge—such as labeled nodes or pairwise constraints—into the detection process to guide the identification of community structures in networks.
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2.4K
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148
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80
Institutions
Publications per year
2017–2026
28
Parents
Publications
50
Modularity based community detection with deep learning
Liang Yang, Xiaochun Cao, Dongxiao He et al. · 2016 · 172 citations
Di Jin, Ziyang Liu, Weihao Li et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 2019 · 139 citations · Full text
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Authors
148
- DJ
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- DH
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- XC
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- XM
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- LY
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1–5 of 148
Institutions
80
Tianjin University
Tianjin, China
6 h-index
19 publications
1.4K citations
Chinese Academy of Sciences
Beijing, China
6 h-index
12 publications
1.2K citations
Tianjin University of Commerce
Tianjin, China
4 h-index
4 publications
410 citations
Henan Normal University
Xinxiang, China
4 h-index
9 publications
214 citations
Xidian University
Xi'an, China
4 h-index
9 publications
727 citations
Institute of Information Engineering
Beijing, China
4 h-index
10 publications
1.2K citations
Tianjin University of Science and Technology
Tianjin, China
3 h-index
8 publications
230 citations
Fudan University
Shanghai, China
3 h-index
12 publications
677 citations
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Venues
- Physica A Statistical Mechanics and its Applications
4 publications · 218 citations
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- Scientific Reports
3 publications · 100 citations
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- Journal of Statistical Mechanics Theory and Experiment
JSTAT · 2 publications · 25 citations
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- Europhysics Letters (EPL)
2 publications · 93 citations
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- IEEE Transactions on Knowledge and Data Engineering
TKDE · 2 publications · 177 citations
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