Relaxing time granularity for mining frequent sequences

Abstract

In an industrial context application aiming at performing aeronautic maintenance tasks scheduling, 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 to validate our proposal. © 2014 Springer International Publishing Switzerland.