PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets

Daniel A. Keim, Christian Panse, Mike Sips, Stephen C. North

Abstract: 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.