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

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