Multi-level clustering and its visualization for exploratory spatial analysis
Estivill-Castro, Vladimir, and Lee, Ickjai (2002) Multi-level clustering and its visualization for exploratory spatial analysis. Geoinformatica, 6 (2). pp. 123-152.
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Exploratory spatial analysis is increasingly necessary as larger spatial data is managed in electro-magnetic media. We propose an exploratory method that reveals a robust clustering hierarchy from two-dimensional point data. Our approach uses the Delaunay diagram to incorporate spatial proximity. It does not require prior knowledge about the data set, nor does it require preconditions. Multi-level clusters are successfully discovered by this new method in only O(nlogn) time, where n is the size of the data set. The efficiency of our method allows us to construct and display a new type of tree graph that facilitates understanding of the complex hierarchy of clusters. We show that clustering methods adopting a raster-like or vector-like representation of proximity are not appropriate for spatial clustering. We conduct an experimental evaluation with synthetic data sets as well as real data sets to illustrate the robustness of our method.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||Clustering, Data mining, Exploratory spatial analysis, Delaunay diagram, Cluster visualization|
© 2002 Springer : The original publication is available at SpringerLink (use hypertext links above) http://www.springerlink.com
|Date Deposited:||11 Sep 2006|
|FoR Codes:||09 ENGINEERING > 0909 Geomatic Engineering > 090903 Geospatial Information Systems @ 50%
08 INFORMATION AND COMPUTING SCIENCES > 0806 Information Systems > 080604 Database Management @ 50%
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