Attributed Community Detection
Attributed Community Detection is a community detection paradigm that extends traditional graph-based clustering by incorporating node or edge attributes to identify densely connected groups of nodes while simultaneously considering the homogeneity of their associated attribute information.
54
Publications
2.5K
Citations
181
Authors
102
Institutions
Publications per year
2017–2026
47
Parents
54
Attribute-driven community search
Xin Huang, Laks V. S. Lakshmanan · Proceedings of the VLDB Endowment · 2017 · 241 citations
Clustering attributed graphs: Models, measures and methods
Cécile Bothorel, Juan David Cruz Gomez, Matteo Magnani et al. · Network Science · 2015 · 240 citations · Full text
Community Detection in Attributed Graphs: An Embedding Approach
Li Ye, Chaofeng Sha, Xin Huang et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 2018 · 236 citations · Full text
Computing, Data Science, Data Mining +10
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102

Xidian University
Xi'an, China
4 h-index
10 publications
834 citations
Université Sorbonne Paris Nord
Villetaneuse, France
3 h-index
9 publications
262 citations
Hong Kong Baptist University
Hong Kong, Hong Kong
3 h-index
3 publications
496 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
6 publications
531 citations
University of Technology Sydney
Sydney, Australia
3 h-index
3 publications
61 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
3 h-index
11 publications
721 citations

City University of Hong Kong
Hong Kong, Hong Kong
2 h-index
2 publications
53 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
5 publications
298 citations
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4 publications · 273 citations
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3 publications · 148 citations
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2 publications · 32 citations
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2 publications · 50 citations
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2 publications · 100 citations
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