• DOI:10.1023/A:1009769707641
Corpus ID: 11323096

Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values

@article{Huang2004ExtensionsTT,
  title={Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values},
  author={J. Huang},
  journal={Data Mining and Knowledge Discovery},
  year={2004},
  volume={2},
  pages={283-304}
}

J. Huang

Published 2004

Mathematics, Computer Science

Data Mining and Knowledge Discovery

The k-means algorithm is well known for its efficiency in clustering large data sets. However, working only on numeric values prohibits it from being used to cluster real world data containing categorical values. In this paper we present two algorithms which extend the k-means algorithm to categorical domains and domains with mixed numeric and categorical values. The k-modes algorithm uses a simple matching dissimilarity measure to deal with categorical objects, replaces the means of clusters… CONTINUE READING

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