An apriori-based algorithm for mining semi-order-preserving submatrix

Abstract

Order-preserving submatrices OPSMs find objects that exhibit a coherent pattern with the same linear ordering in subspace. In general, this problem can be reducible to a special case of the sequential pattern mining problem, where a pattern and its supporting sequences uniquely specify an OPSM. In this paper, we extend the idea of order-preserving submatrix and define a new model semi-order-preserving submatrix or SOPSM that can be generalised to cover most existing bicluster models, and then propose a novel exact algorithm for mining all significant SOPSMs. To reduce the computational costs, we further propose a pruning technique and design an improved data structure for prefix tree to speed up the running time of the algorithm. A set of extensive experiments have been performed which demonstrate the effectiveness and efficiency of our method in mining SOPSMs.