DocumentCode
2370518
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
fYear
2003
fDate
19-22 Nov. 2003
Firstpage
565
Lastpage
568
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
Print_ISBN
0-7695-1978-4
Type
conf
DOI
10.1109/ICDM.2003.1250978
Filename
1250978
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