Community Pattern Discovery
Community Pattern Discovery is a methodological framework within community visualization that identifies and characterizes recurrent structural and behavioral motifs in community-organized data by integrating computational detection techniques with interpretative visual analytics to reveal meaningful, latent patterns in social or networked entities.
41
Publications
2.9K
Citations
134
Authors
81
Institutions
Publications per year
2017–2026
12
Parents
41
Patternizing communities by using an artificial neural network
Tae‐Soo Chon, Young‐Seuk Park, Kyong Hi Moon et al. · Ecological Modelling · 1996 · 294 citations
Albert Park, Mike Conway, Annie Chen · Computers in Human Behavior · 2017 · 227 citations · Full text
Uncoverning Groups via Heterogeneous Interaction Analysis
Lei Tang, Xufei Wang, Huan Liu · 2009 · 166 citations
CAP: community activity prediction based on big data analysis
Yin Zhang⋆, Min Chen, Shiwen Mao et al. · IEEE Network · 2014 · 154 citations
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81
University of Kassel
Kassel, Germany
4 h-index
5 publications
140 citations
Arizona State University
Tempe, United States
2 h-index
4 publications
521 citations
University of California, Riverside
Riverside, United States
2 h-index
5 publications
82 citations
GE Global Research (United States)
Niskayuna, United States
2 h-index
8 publications
392 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
4 publications
312 citations
University of Zurich
Zurich, Switzerland
2 h-index
2 publications
108 citations
Neu-Ulm University of Applied Sciences
Neu-Ulm, Germany
1 h-index
1 publications
17 citations

University of Pisa
Pisa, Italy
1 h-index
3 publications
282 citations
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2 publications · 35 citations
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2 publications · 387 citations
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2 publications · 126 citations
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Conference · 2 publications · 98 citations
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1 publications · 34 citations
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