TSRuleGrowth : Extraction de r\`egles de pr\'ediction semi-ordonn\'ees \`a partir d'une s\'erie temporelle d'\'el\'ements discrets, application dans un contexte d'intelligence ambiante

This paper presents a new algorithm: TSRuleGrowth, looking for partially-ordered rules over a time series. This algorithm takes principles from the state of the art of rule mining and applies them to time series via a new notion of support. We apply this algorithm to real data from a connected environment, which extract user habits through different connected objects.