Map segmentation for geospatial data mining through generalized higher-order Voronoi diagrams with sequential scan algorithms

Lee, Ickjai, Torpelund-Bruin, Christopher, and Lee, Kyungmi (2012) Map segmentation for geospatial data mining through generalized higher-order Voronoi diagrams with sequential scan algorithms. Expert Systems with Applications, 39 (12). pp. 11135-11148.

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Abstract

Segmentation is one popular method for geospatial data mining. We propose efficient and effective sequential-scan algorithms for higher-order Voronoi diagram districting. We extend the distance transform algorithm to include complex primitives (point, line, and area), Minkowski metrics, different weights and obstacles for higher-order Voronoi diagrams. The algorithm implementation is explained along with efficiencies and error. Finally, a case study based on trade area modeling is described to demonstrate the advantages of our proposed algorithms.

Item ID: 23353
Item Type: Article (Refereed Research - C1)
ISSN: 0957-4174
Date Deposited: 10 Sep 2012 02:13
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems @ 50%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 50%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890202 Application Tools and System Utilities @ 50%
89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 50%
Citation Count from Web of Science Web of Science 2
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