Sequence mining in categorical domains

Abstract

We present cSPADE, an efficient algorithm for mining frequent sequences considering a variety of syntactic constraints. These take the form of length or width limitations on the sequences, minimum or maximum gap constraints on consecutive sequence elements, applying a time window on allowable sequences, incorporating item constraints, and finding sequences predictive of one or more classes, even rare ones. Our method is efficient and scalable. Experiments on a number of synthetic and real databases show the utility and performance of considering such constraints on the set of mined sequences.