A Similarity Measure for Clustering and its Applications
Authors
Abstract
This paper introduces a measure of similarity between two clusterings of the samedataset produced by two different algorithms, or even the same algorithm (K-means, for
instance, with different initializations usually produce different results in clustering the same dataset). We then apply the measure to calculate the similarity between pairs of clusterings, with special interest directed at comparing the similarity between various machine clusterings and human clustering of datasets.