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Visualizing High Dimensional Datasets Using Partiview
Austin, Texas October 10-October 12
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/INFVIS.2004.762004 IEEE Symposium on Information Vi ...
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Dinoj Surendran, University of Chicago
Stuart Levy, University of Illinois at Urbana-Champaign
A standard method of visualizing high-dimensional data is reducing its dimensionality to two or three using some algorithm, and then creating a scatterplot with data represented by labelled and/or colored dots. Two problems with this approach are (1) dots do not represent data well, (2) reducing to just three dimensions does not make full use of several dimensionality-reduction algorithms. We demonstrate how Partiview can be used to solve these problems, in the context of handwriting recognition and image retrieval.
Index Terms:
dimensionality reduction, glyphs, high dimensional data visualization, optical character recognition, image retrieval, information visualization
Citation:
Dinoj Surendran, Stuart Levy, "Visualizing High Dimensional Datasets Using Partiview," infovis, pp.p20, 2004 IEEE Symposium on Information Visualization (InfoVis 2004), 2004
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