This paper proposes an interactive pattern mining method assuming that only some trans- actions are interesting for the user. By integrating his feedback, our method aims at sampling patterns with a probability proportional to their frequency in these preferred transactions. We demonstrate that our method accurately identifies the preferred transactions if user feedback are consistent. Experiments show the good performances of the approach.