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- W2023179464 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." @default.
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- W2023179464 date "2012-09-01" @default.
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- W2023179464 title "Map segmentation for geospatial data mining through generalized higher-order Voronoi diagrams with sequential scan algorithms" @default.
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- W2023179464 doi "https://doi.org/10.1016/j.eswa.2012.03.042" @default.
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