A hierarchical clustering algorithm for categorical sequence data

Recently, there has been enormous growth in the amount of commercial and scientific data, such as protein sequences, retail transactions, and web-logs. In this paper, we study how to cluster these sequence datasets. We propose a new similarity measure to compute the similarity between two sequences and develop a hierarchical clustering algorithm. Using a splice dataset and synthetic datasets, we show that the quality of clusters generated by our proposed approach is better than that of clusters produced by traditional clustering algorithms. (C) 2004 Elsevier B.V. All rights reserved.