Relaxing Time Granularity for Mining Frequent Sequences

International audienceIn 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. Advances in Knowledge Discovery and Management Advances in Knowledge Discovery and Management Look Insid