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ICDM
2003
IEEE
138views Data Mining» more  ICDM 2003»
13 years 10 months ago
PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets
PixelMaps are a new pixel-oriented visual data mining technique for large spatial datasets. They combine kerneldensity-based clustering with pixel-oriented displays to emphasize c...
Daniel A. Keim, Christian Panse, Mike Sips, Stephe...
IEEEVAST
2010
12 years 11 months ago
Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological opera
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each ob...
Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott Trager...
VL
1996
IEEE
157views Visual Languages» more  VL 1996»
13 years 8 months ago
Visualizing Program Executions on Large Data Sets
Understanding and interpreting a large data source is an important but challenging operation in many technical disciplines. Computer visualization has become a valuable tool to he...
John T. Stasko, Jeyakumar Muthukumarasamy
BMCBI
2010
125views more  BMCBI 2010»
13 years 4 months ago
NeatMap - non-clustering heat map alternatives in R
Background: The clustered heat map is the most popular means of visualizing genomic data. It compactly displays a large amount of data in an intuitive format that facilitates the ...
Satwik Rajaram, Yoshi Oono
VIS
2009
IEEE
205views Visualization» more  VIS 2009»
14 years 5 months ago
Time and Streak Surfaces for Flow Visualization in Large Time-Varying Data Sets
Time and streak surfaces are ideal tools to illustrate time-varying vector fields since they directly appeal to the intuition about coherently moving particles. However, efficient ...
Hari Krishnan, Christoph Garth, Kenneth I. Joy