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

Two algorithms which extend the k-means algorithm to categorical domains and domains with mixed numeric and categorical values are presented and are shown to be efficient when clustering large data sets, which is critical to data mining applications.