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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2018
    • vol. 5, nº 3, december 2018
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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2018
    • vol. 5, nº 3, december 2018
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    An Adapted Approach for User Profiling in a Recommendation System: Application to Industrial Diagnosis

    Autor: 
    Taghezout, Noria
    ;
    Benkaddour, Fatima Zohra
    ;
    Kaddour-Ahmed, Fatima Zahra
    ;
    Hammadi, Ilyes-Ahmed
    Fecha: 
    12/2018
    Palabra clave: 
    recommendation systems; DSS; twitter; collaborative filtering; industrial diagnosis; IJIMAI
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/12404
    DOI: 
    http://doi.org/10.9781/ijimai.2018.06.003
    Dirección web: 
    https://www.ijimai.org/journal/bibcite/reference/2678
    Open Access
    Resumen:
    In 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.
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