Uncertainty interval temporal sequences extraction

Abstract

Searching for frequent sequential patterns has been used in several domains. We note that times granularities are more or less important with regards to the application domain. In this paper we propose a frequent interval time sequences (ITS) extraction technique from discrete temporal sequences using a sliding window approach to relax time constraints. The extracted sequences offer an interesting overview of the original data by allowing a temporal leeway on the extraction process. We formalize the ITS extraction under classical time and support constraints and conduct some experiments on synthetic data for validating our proposal. © 2012 Springer-Verlag.