Bernard, Jürgen ; Landesberger von Antburg, Tatiana ; Bremm, Sebastian ; Schreck, Tobias (2010)
Cluster Correspondence Views for Enhanced Analysis of SOM Displays.
IEEE Conference on Visual Analytics Science and Technology 2010. Proceedings.
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
The Self-Organizing Map (SOM) algorithm is a popular and widely used cluster algorithm. Its constraint to organize clusters on a grid structure makes it very amenable to visualization. On the other hand, the grid constraint may lead to reduced cluster accuracy and reliability, compared to other clustering methods not implementing this restriction. We propose a visual cluster analysis system that allows to validate the output of the SOM algorithm by comparison with alternative clustering methods. Specifically, visual mappings overlaying alternative clustering results onto the SOM are proposed. We apply our system on an example data set, and outline main analytical use cases.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2010 |
| Autor(en): | Bernard, Jürgen ; Landesberger von Antburg, Tatiana ; Bremm, Sebastian ; Schreck, Tobias |
| Art des Eintrags: | Bibliographie |
| Titel: | Cluster Correspondence Views for Enhanced Analysis of SOM Displays |
| Sprache: | Englisch |
| Publikationsjahr: | 2010 |
| Verlag: | IEEE Press, New York |
| Veranstaltungstitel: | IEEE Conference on Visual Analytics Science and Technology 2010. Proceedings |
| Kurzbeschreibung (Abstract): | The Self-Organizing Map (SOM) algorithm is a popular and widely used cluster algorithm. Its constraint to organize clusters on a grid structure makes it very amenable to visualization. On the other hand, the grid constraint may lead to reduced cluster accuracy and reliability, compared to other clustering methods not implementing this restriction. We propose a visual cluster analysis system that allows to validate the output of the SOM algorithm by comparison with alternative clustering methods. Specifically, visual mappings overlaying alternative clustering results onto the SOM are proposed. We apply our system on an example data set, and outline main analytical use cases. |
| Freie Schlagworte: | Forschungsgruppe Visual Search and Analysis (VISA), Visual analytics, Cluster analysis, Self-organizing maps (SOM), Quality measurements |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 22 Jul 2021 18:31 |
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