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• W2022244837 abstract "In this paper, we generalize the k-modes clustering algorithm by weighting attribute value in the dissimilarity computation. Such a generalization generates clusters with stronger intra-similarities, leading to better clustering performance. Experimental results on real life data show that the new k-modes algorithm is superior to the standard k-modes algorithm with respect to clustering accuracy." @default.
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• W2022244837 date "2011-11-01" @default.
• W2022244837 modified "2023-09-25" @default.
• W2022244837 title "Attribute value weighting in k-modes clustering" @default.
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• W2022244837 doi "https://doi.org/10.1016/j.eswa.2011.06.027" @default.
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