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Please use this identifier to cite or link to this item: http://hdl.handle.net/2014/37939

Title: Visual data mining for quantized spatial data
Authors: Braverman, Amy
Kahn, Brian
Keywords: massive data sets
cluster analysis
multivariate visualization
Issue Date: Aug-2004
Publisher: Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2004.
Citation: COMPSTAT 2004, The 16th Symposium of IASC, Prague, Czech Republic, August 23, 2004
Abstract: In previous papers we've shown how a well known data compression algorithm called Entropy-constrained Vector Quantization ( can be modified to reduce the size and complexity of very large, satellite data sets. In this paper, we descuss how to visualize and understand the content of such reduced data sets.
URI: http://hdl.handle.net/2014/37939
Appears in Collections:JPL TRS 1992+

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