Department of Software Technology
Vienna University of Technology
On the Similarity of Eagles, Hawks, and Cows:
Visualization of Semantic Similarity in Self-Organizing Maps
Abstract: We describe an extension to the self-organizing map learning rule enabeling a straight-forward visual representation of input data similarity in high-dimensional input structures. The general idea of the extension is to mirror the movement of weight vectors during the training process within a two-dimensional (virtual) output space. The result of the extended training algorithm allows intuitive analysis of the similarities inherent in the input data and most important, intuitive recognition of cluster boundaries.
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Comments: rauber@ifs.tuwien.ac.at