Self-organizing Map Visualization
Self-Organizing Map Visualization is a dimensionality reduction and data visualization technique that projects high-dimensional data onto a low-dimensional regular grid of nodes, preserving topological relationships through competitive learning and neighborhood-based adaptation.
285
Publications
14.2K
Citations
642
Authors
311
Institutions
Publications per year
2017–2026
31
285
Engineering applications of the self-organizing map
Teuvo Kohonen, Erkki Oja, Olli Simula et al. · Proceedings of the IEEE · 1996 · 850 citations
SOM-based data visualization methods
Juha Vesanto · Intelligent Data Analysis · 1999 · 744 citations
Analysis of gene expression data using self‐organizing maps
Petri Törönen, Mikko Kolehmainen, Garry Wong et al. · FEBS Letters · 1999 · 550 citations · Full text
WEBSOM – Self-organizing maps of document collections
Samuel Kaski, Timo Honkela, Krista Lagus et al. · Neurocomputing · 1998 · 495 citations
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University of Helsinki
Helsinki, Finland
11 h-index
32 publications
4.1K citations
Åbo Akademi University
Turku, Finland
10 h-index
15 publications
457 citations
Turku Centre for Computer Science
Turku, Finland
7 h-index
11 publications
283 citations

Tohoku University
Sendai, Japan
6 h-index
17 publications
678 citations

Oklahoma State University
Stillwater, United States
4 h-index
9 publications
141 citations
Fraunhofer Institute for Computer Graphics Research
Darmstadt, Germany
4 h-index
4 publications
303 citations
The University of Tokyo
Tokyo, Japan
4 h-index
9 publications
275 citations

Johannes Kepler University of Linz
Linz, Austria
4 h-index
14 publications
621 citations
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10 publications · 1.3K citations
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4 publications · 273 citations
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Repository · 4 publications · 169 citations
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4 publications · 558 citations
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3 publications · 176 citations
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