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Your search keyword '"Delphin-Poulat, Lionel"' showing total 10 results
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10 results on '"Delphin-Poulat, Lionel"'

1. 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

Author

Vuillemin, Benoit, Delphin-Poulat, Lionel, Nicol, Rozenn, Matignon, Laëtitia, and Hassas, Salima

Subjects
Computer Science - Artificial Intelligence
Abstract

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., Comment: in French. Conf\'erence Nationale sur les Applications Pratiques de l'Intelligence Artificielle (APIA), Jul 2019, Toulouse, France

Published
2019

2. TSRuleGrowth: Mining Partially-Ordered Prediction Rules From a Time Series of Discrete Elements, Application to a Context of Ambient Intelligence

Author

Vuillemin, Benoit, Delphin-Poulat, Lionel, Nicol, Rozenn, Matignon, Laetitia, Hassas, Salima, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Li, Jianxin, editor, Wang, Sen, editor, Qin, Shaowen, editor, Li, Xue, editor, and Wang, Shuliang, editor

Published
2019
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5. 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

Author

Vuillemin, Benoit, Delphin-Poulat, Lionel, Nicol, Rozenn, Matignon, Laëtitia, and Hassas, Salima

Subjects
Computer Science - Artificial Intelligence
Abstract

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., Comment: in French. Conf\'erence Nationale sur les Applications Pratiques de l'Intelligence Artificielle (APIA), Jul 2019, Toulouse, France

Published
2019

6. TSRuleGrowth : Extraction de r��gles de pr��diction semi-ordonn��es �� partir d'une s��rie temporelle d'��l��ments discrets, application dans un contexte d'intelligence ambiante

Author

Vuillemin, Benoit, Delphin-Poulat, Lionel, Nicol, Rozenn, Matignon, La��titia, and Hassas, Salima

Subjects
FOS: Computer and information sciences, Artificial Intelligence (cs.AI)
Abstract

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., in French. Conf\'erence Nationale sur les Applications Pratiques de l'Intelligence Artificielle (APIA), Jul 2019, Toulouse, France

Published
2019
Full Text
View/download PDF

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