dc.creatorTaghezout, Noria
dc.creatorBenkaddour, Fatima Zohra
dc.creatorKaddour-Ahmed, Fatima Zahra
dc.creatorHammadi, Ilyes-Ahmed
dc.date.accessioned2022-02-07T12:14:44Z
dc.date.accessioned2023-03-07T19:34:35Z
dc.date.available2022-02-07T12:14:44Z
dc.date.available2023-03-07T19:34:35Z
dc.date.created2022-02-07T12:14:44Z
dc.identifier1989-1660
dc.identifierhttps://reunir.unir.net/handle/123456789/12404
dc.identifierhttp://doi.org/10.9781/ijimai.2018.06.003
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5906700
dc.description.abstractIn this paper, we propose a global architecture of a recommender tool, which represents a part of an existing collaborative platform. This tool provides diagnostic documents for industrial operators. The recommendation process considered here is composed of three steps: Collecting and filtering information; Prediction or recommendation step; evaluating and improvement. In this work, we focus on collecting and filtering step. We mainly use information result from collaborative sessions and documents describing solutions that are attributed to the complex diagnostic problems. The developed tool is based on collaborative filtering that operates on users' preferences and similar responses.
dc.languageeng
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)
dc.relation;vol. 5, nº 3
dc.relationhttps://www.ijimai.org/journal/bibcite/reference/2678
dc.rightsopenAccess
dc.subjectrecommendation systems
dc.subjectDSS
dc.subjecttwitter
dc.subjectcollaborative filtering
dc.subjectindustrial diagnosis
dc.subjectIJIMAI
dc.titleAn Adapted Approach for User Profiling in a Recommendation System: Application to Industrial Diagnosis
dc.typearticle


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