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Third IEEE International Conference on Data Mining (ICDM'03)
PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets
Melbourne, Florida
November 19-November 22
ISBN: 0-7695-1978-4
Daniel A. Keim, University of Konstanz, Germany
Christian Panse, University of Konstanz, Germany
Mike Sips, University of Konstanz, Germany
Stephen C. North, AT&T Shannon Laboratory, Florham Park, NJ
PixelMaps are a new pixel-oriented visual data mining technique for large spatial datasets. They combine kernel-density-based clustering with pixel-oriented displays to emphasize clusters while avoiding overlap in locally dense point sets on maps. Because a full evaluation of density functions is prohibitively expensive, we also propose an efficient approximation, Fast-PixelMap, based on a synthesis of the quadtree and gridfile data structures.
Citation:
Daniel A. Keim, Christian Panse, Mike Sips, Stephen C. North, "PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets," icdm, pp.565, Third IEEE International Conference on Data Mining (ICDM'03), 2003
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