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The interval and the density valve are need to input in traditional clustering methods that based on grid and density method, result in unsmoothed cluster, wrong judgment of clustering boundary. A clustering approach was proposed, which can confirm the interval and the number of clustering, reasonable cluster the object and create the Hilbert R-tree using the result of clustering. Experiment result...
Traditional grid-density based spatial clustering algorithms divide input data space into partitions with same width and neglect the natural distributing character of initial data space. A new robust spatial clustering algorithm based on optimized-division (OpD-Clus) is proposed in this paper. Spatial data space is divided by hyper-planes which are encertained with axis-paralleled histogram in OpD-Clus...
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