Cluster Exploration
Cluster Exploration is a methodological framework within cluster visualization and network exploration that systematically identifies, characterizes, and interprets coherent substructures in complex networks by integrating topological analysis with semantic labeling to facilitate meaningful, human-centric understanding of clustered data regions.
65
Publications
3.6K
Citations
245
Authors
124
Institutions
Publications per year
2017–2026
14
65
Yizhou Sun, Brandon Norick, Jiawei Han et al. · ACM Transactions on Knowledge Discovery from Data · 2013 · 173 citations
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124

Centre National de la Recherche Scientifique
Paris, France
4 h-index
20 publications
746 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
14 publications
1.7K citations
University of Illinois Chicago
Chicago, United States
3 h-index
3 publications
414 citations
University of California, Santa Barbara
Santa Barbara, United States
3 h-index
3 publications
414 citations
Harvard University
Cambridge, United States
2 h-index
2 publications
38 citations
Boston University
Boston, United States
2 h-index
2 publications
262 citations
Laboratoire Bordelais de Recherche en Informatique
Talence, France
2 h-index
4 publications
53 citations
University of Konstanz
Konstanz, Germany
2 h-index
5 publications
347 citations
1–8 of 124
TVCG · 6 publications · 331 citations
6
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2 publications · 83 citations
2
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2 publications · 27 citations
2
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TKDD · 2 publications · 203 citations
2
h-index
1 publications · 24 citations
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