Spatialization Design: Comparing Points and Landscapes
IEEE Transactions on Visualization and Computer Graphics
Topology preservation in self-organizing feature maps: exact definition and measurement
IEEE Transactions on Neural Networks
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Spatialization methods create visualizations that allow users to analyze high-dimensional data in an intuitive manner and facilitates the extraction of meaningful information. Just as geographic maps are simplified representations of geographic spaces, these visualizations are essentially maps of abstract data spaces that are created through dimensionality reduction.Recently, we proposed to use the spherical Geodesic SOM for creating an information landscape that represents an abstract data space and can capture a manifold's global structure. Path finding was then applied to approximate the geodesic path in the feature space and some promising preliminary results were obtained. Based on these results, we propose a novel approach for measuring the preservation of geodesics by analyzing the paths on the information landscapes. The effectiveness of the measure is then evaluated through various data sets.