Discriminating Subsequence Discovery for Sequence Clustering

In this paper, we explore the discriminating subsequence-based clustering problem. First, several effective optimiza-tion techniques are proposed to accelerate the sequence min-ing process and a new algorithm, CONTOUR, is developed to efficiently and directly mine a subset of discriminating frequent subsequences which can be used to cluster the in-put sequences. Second, an accurate hierarchical clustering algorithm, SSC, is constructed based on the result of CON-TOUR. The performance study evaluates the efficiency and scalability of CONTOUR, and the clustering quality of SSC