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Revising K-Means Clustering under Semi-Supervision
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 Title & Authors
Revising K-Means Clustering under Semi-Supervision
Huh Myung-Hoe; Yi SeongKeun; Lee Yonggoo;
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In k-means clustering, we standardize variables before clustering and iterate two steps: units allocation by Euclidean sense and centroids updating. In applications to DB marketing where clusters are to be used as customer segments with similar consumption behaviors, we frequently acquire additional variables on the customers or the units through marketing campaigns a posteriori. Hence we need to modify the clusters originally formed after each campaign. The aim of this study is to propose a revision method of k-means clusters, incorporating added information by weighting clustering variables. We illustrate the proposed method in an empirical case.
k-means clustering;customer segmentation;weighting variables;entropy criterion;marketing campaign;
 Cited by
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