First-order temporal pattern mining with regular expression constraints

Previous studies on mining sequential patterns have focused on temporal patterns specified by some form of propositional temporal logic. However, there are some interesting sequential patterns whose specification needs a more expressive formalism, the first-order temporal logic. Multi-sequential patterns are first-order temporal patterns and aim at representing the behaviour of individuals related to each other by some criteria, throughout time. They appear in many application domains, like financial market and retailing. In this paper, we extend a well-known user-controlled tool, based on regular expressions constraints, to the multi-sequential pattern context. This specification tool enables the incorporation of user focus into the multi-sequential patterns mining process. We present MSP-Miner, an Apriori-based algorithm to discover all frequent multi-sequential patterns satisfying a user-specified regular expression constraint. We perform detailed experiments on synthetic data to study the performance of MSP-Miner

First-order temporal pattern mining with regular expression constraints

Abstract. Previous studies on mining sequential patterns have focused on temporal patterns specified by some form of propositional temporal logic. However, there are some interesting sequential patterns, such as the multi-sequential patterns, whose specification needs a more expressive formalism, the first-order temporal logic. In this paper, we extend a well-known user-controlled tool, based on regular expressions constraints, to the multi-sequential pattern context. This specification tool enables the incorporation of user focus into the multi-sequential patterns mining process. We present MSP-Miner, an Aprioribased algorithm to discover all frequent multi-sequential patterns satisfying a user-specified regular expression constraint. 1