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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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 Type:||Article (Refereed Research - C1)|
|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%
|Deposited On:||10 Sep 2012 12:13|
|Last Modified:||19 Jun 2013 02:04|
Last 12 Months: 1
|Citation Counts with External Providers:||Web of Science: 0|
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