Categorical Data Clustering: A Bibliometric Analysis and Taxonomy
Maya Cendana,
Ren-Jieh Kuo
Abstract:Numerous real-world applications apply categorical data clustering to find hidden patterns in the data. The K-modes-based algorithm is a popular algorithm for solving common issues in categorical data, from outlier and noise sensitivity to local optima, utilizing metaheuristic methods. Many studies have focused on increasing clustering performance, with new methods now outperforming the traditional K-modes algorithm. It is important to investigate this evolution to help scholars understand how the existing alg… Show more
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