Discriminating Subsequence Discovery for Sequence Clustering

In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining 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 input sequences. Second, an accurate hierarchical clustering algorithm, SSC, is constructed based on the result of CONTOUR. The performance study evaluates the efficiency and scalability of CONTOUR, and the clustering quality of SSC. Keywords. Sequence mining, summarization subsequence, clustering.

• Type: Conference
• Year: 2007
• Where: SDM
• Authors: Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Karypis, Charu C. Aggarwal
• Keywords: Data Mining, Hierarchical Clustering Algorithm, SDM 2007, Sequence Mining, Subsequencebased Clustering Problem