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Apprentissage de comportements à partir de données temporelles hétérogènes

Nida Meddouri 1 François Rioult 1 Bruno Crémilleux 1 
1 Equipe CODAG - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
Abstract : Recently, the learning of a behavior from temporal data has been the subject of several research works. The approaches and techniques of temporal data mining are tools that make it possible to model a behavior. From a patient room in a hospital, we propose to save a trace of the student actions and the state of each object in this room at any time. This trace will make it possible to model the behavior of a student in the form of induction rules set. The analysis and comparison of rules sets generated will make it possible to compare and group the behaviors of several learners and to deduce a typical behavior among those most similar.
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Submitted on : Monday, July 25, 2022 - 5:59:58 PM
Last modification on : Thursday, August 4, 2022 - 3:31:37 AM


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  • HAL Id : hal-03738180, version 1


Nida Meddouri, François Rioult, Bruno Crémilleux. Apprentissage de comportements à partir de données temporelles hétérogènes. Conférence francophone sur l'Extraction et la Gestion des Connaissances, Association EGC, Jan 2022, Blois, France. pp.77-79. ⟨hal-03738180⟩



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