Intelligent Digital Learning: Agent-Based Recommender System

Imène Brigui-Chtioui 1 Philippe Caillou 2 Elsa Negre 3
2 TAU - TAckling the Underspecified
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : In the context of intelligent digital learning, we propose an agent-based recommender system that aims to help learners overcome their gaps by suggesting relevant learning resources. The main idea is to provide them with appropriate support in order to make their learning experience more effective. To this end we design an agent-based cooperative system where autonomous agents are able to update recommendation data and to improve the recommender outcome on behalf of their past experiences in the learning platform. CCS Concepts • Information systems➝Information retrieval ➝Retrieval tasks and goals ➝ Recommender systems.
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Communication dans un congrès
ICMLC 2017 - 9th International Conference on Machine Learning and Computing, Feb 2017, Singapore, Singapore. 〈10.1145/3055635.3056592〉
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Imène Brigui-Chtioui, Philippe Caillou, Elsa Negre. Intelligent Digital Learning: Agent-Based Recommender System. ICMLC 2017 - 9th International Conference on Machine Learning and Computing, Feb 2017, Singapore, Singapore. 〈10.1145/3055635.3056592〉. 〈hal-01680527〉

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