Dissimilarity Matrix Visualization
Dissimilarity Matrix Visualization is a visualization technique that encodes pairwise dissimilarities among objects in a multidimensional space into a two-dimensional matrix representation, distinguished by its explicit spatial arrangement of entries to reveal structural patterns such as clusters, gradients, or outliers in the underlying dissimilarity data.
18
Publications
1.5K
Citations
39
Authors
24
Institutions
Publications per year
2017–2026
2
18
VAT: a tool for visual assessment of (cluster) tendency
James C. Bezdek, Richard J. Hathaway · 2003 · 336 citations
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24

Georgia Southern University
Statesboro, United States
2 h-index
2 publications
427 citations

The University of Melbourne
Melbourne, Australia
2 h-index
4 publications
178 citations

University of West Florida
Pensacola, United States
2 h-index
3 publications
518 citations
Ben-Gurion University of the Negev
Beersheba, Israel
1 h-index
3 publications
33 citations

Monash University
Melbourne, Australia
1 h-index
1 publications
45 citations
Nomura Holdings (Japan)
Tokyo, Japan
1 h-index
2 publications
66 citations

Universidad Pontificia de Salamanca
Salamanca, Spain
1 h-index
1 publications
16 citations

Pennsylvania State University
State College, United States
1 h-index
6 publications
1.9K citations
1–8 of 24
JCGS · 2 publications · 327 citations
2
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2 publications · 105 citations
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1 publications · 27 citations
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1 publications · 26 citations
1
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TKDE · 1 publications · 45 citations
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