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

I
ICDM
2003
Third IEEE International Conference on Data Mining (ICDM'03)
Abstract - PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets

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Third IEEE International Conference on Data Mining (ICDM'03)

Melbourne, Florida

November 19-November 22

ISBN: 0-7695-1978-4

	ASCII Text	x
	Daniel A. Keim, Christian Panse, Mike Sips, Stephen C. North, "PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets," Data Mining, IEEE International Conference on, pp. 565, Third IEEE International Conference on Data Mining (ICDM'03), 2003.

	BibTex	x
	@article{ 10.1109/ICDM.2003.1250978, author = {Daniel A. Keim and Christian Panse and Mike Sips and Stephen C. North}, title = {PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2003}, isbn = {0-7695-1978-4}, pages = {565}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1250978}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining, IEEE International Conference on TI - PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets SN - 0-7695-1978-4 SP EP A1 - Daniel A. Keim, A1 - Christian Panse, A1 - Mike Sips, A1 - Stephen C. North, PY - 2003 KW - null VL - 0 JA - Data Mining, IEEE International Conference on ER -

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

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1250978

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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