Paper
11 March 2005 Geodesic self-organizing map
Yingxin Wu, Masahiro Takatsuka
Author Affiliations +
Proceedings Volume 5669, Visualization and Data Analysis 2005; (2005) https://doi.org/10.1117/12.586807
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
Self-Organizing map (SOM) is a widely used tool to find clustering and also to visualize high dimensional data. Several spherical SOMs have been proposed to create a more accurate representation of the data by removing the “border effect”. In this paper, we compare several spherical lattices for the purpose of implementation of a SOM. We then introduce a 2D rectangular grid data structure for representing the geodesic dome. This new approach improves the neighborhood searching process in the spherical gird. The new Geodesic SOM and its data structure are tested using socio-demographic data. In the experiments, we try to create a notion of direction in the Geodesic SOM. The direction facilitates more consistent visual comparison of different datasets as well as to assist viewers building their mental maps.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yingxin Wu and Masahiro Takatsuka "Geodesic self-organizing map", Proc. SPIE 5669, Visualization and Data Analysis 2005, (11 March 2005); https://doi.org/10.1117/12.586807
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CITATIONS
Cited by 13 scholarly publications.
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KEYWORDS
Spherical lenses

Neurons

Optical spheres

Visualization

Data modeling

Associative arrays

Data analysis

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