01446nas a2200253   4500000000100000000000100001008004100002260001200043653002700055653000800082653001200090653002800102653002500130100002000155700002800175700003100203700002400234245010700258856009600365300001200461490000600473520069900479022001401178       2018                            d  c12/201810aRecommendation Systems10aDSS10aTwitter10aCollaborative Filtering10aIndustrial Diagnosis1 aNoria Taghezout1 aFatima Zohra Benkaddour1 aFatima Zahra Kaddour-Ahmed1 aIlyes-Ahmed Hammadi00aAn Adapted Approach for User Profiling in a Recommendation System: Application to Industrial Diagnosis  uhttp://www.ijimai.org/journal/sites/default/files/files/2018/06/ijimai_5_3_13_pdf_15716.pdf  a118-1300 v53 aIn 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.  a1989-1660