Title :
PixelMaps: a new visual data mining approach for analyzing large spatial data sets
Author :
Keim, Daniel A. ; Panse, Christian ; Sips, Mike ; North, Stephen C.
Author_Institution :
Konstanz Univ., Germany
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.
Keywords :
approximation theory; data mining; data visualisation; quadtrees; spatial data structures; visual databases; PixelMap algorithm; fast-PixelMap approximation; gridfile data structure; kernel-density-based clustering; pixel-oriented display; pixel-oriented visual data mining technique; quadtree synthesis; spatial data set analysis; visual data mining; Clustering algorithms; Computer displays; Credit cards; Data analysis; Data mining; Data structures; Data visualization; Density functional theory; Grid computing; Laboratories;
Conference_Titel :
Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
Print_ISBN :
0-7695-1978-4
DOI :
10.1109/ICDM.2003.1250978