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2004

Geo-Spatial Data Viewer: From Familiar Land-covering to Arbitrary Distorted Geo-Spatial Quadtree Maps

10 years 29 days ago
Geo-Spatial Data Viewer: From Familiar Land-covering to Arbitrary Distorted Geo-Spatial Quadtree Maps
In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. A noteworthy trend is the increasing size of data sets in common use, such as records of business transactions, environmental data and census demographics. These data sets often contain millions of records, or even far more. This situation creates new challenges in coping with scale. In this paper we propose a novel pixel-oriented visual data mining approach for large spatial datasets. It combines a quadtree based distortion of map regions and a local reposition of pixels within these map regions to avoid overlap in the display. Experiments shows that it produces visualizations of large data sets for the discovery of local correlations, and is practical for exploring geography-related statistical information in a variety of applications including pop...
Daniel A. Keim, Christian Panse, Jörn Schneid
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where WSCG
Authors Daniel A. Keim, Christian Panse, Jörn Schneidewind, Mike Sips
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