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Chapitre D'ouvrage Année : 2022
ERP and Time Management
1 UT Capitole - Université Toulouse Capitole (2 rue du Doyen-Gabriel-Marty - 31042 Toulouse Cedex 9 - France)
"> UT Capitole - Université Toulouse Capitole
2 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage (Institut de recherche en informatique de Toulouse - IRIT 118 Route de Narbonne 31062 Toulouse Cedex 9 - France)
"> IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage

Résumé

Most of today's companies use management software to support their staff organizing their activity. In this context, this software makes it possible to centralize company data, and to extract useful information from it for users in order to make decisions, such as the organization of their working time. However, the amount of available data is too large for a user to be analyzed on their own. Thus, it is likely that the user will not take the most satisfactory decision according to the criteria imposed by the managers, and the real-time evolution of the activity of the company. In this article, the authors present a recommender system that takes into account the activity of the company, the managers' criteria, as well as the end-user's own criteria in order to guide the user's activities. It can be used for any type of activity sector as soon as data are available. The recommender system is an additional module for an existing ERP. The human-computer interface (HCI) is presented, as well as a database. The system is operable and fully customizable.
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Dates et versions

hal-03965232 , version 1 (31-01-2023)
Identifiants

Citer

Anthony Bronner-Etelin, Pascale Zaraté. ERP and Time Management. Encyclopedia of Data Science and Machine Learning, IGI Global, pp.2781-2798, 2022, Encyclopedia of Data Science and Machine Learning, ⟨10.4018/978-1-7998-9220-5.ch166⟩. ⟨hal-03965232⟩
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