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Algorithm of point cluster similarity based on hierarchical Voronoi diagrams
KANG Shun LI Jiatian
Journal of Computer Applications    2013, 33 (10): 2974-2976.  
Abstract780)      PDF (578KB)(744)       Save
The hierarchical Voronoi diagrams were built through an adaptive clustering method of spatial point clusters. Based on the hierarchical Voronoi diagrams, the topology, density and scope similarities were calculated. The radian and distance similarity were calculated in combination of the standard deviation in mathematical statistics. On the base of every dimensional similarity, the principle of point cluster similarity was decided by the geometrical mean of these parameters. This optimizes the method of the point cluster similarity and the experiment proves its feasibility.
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