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This article presents a comprehensive study of the most important techniques used to handle this issue focusing on AL techniques. The authors then propose a novel item selection approach, based on Multi-Criteria ratings and a method of computing weights of criteria inspired by a multi-criteria decision making approach. This selection method is deployed to learn new users' profiles, to identify the reasons behind which items are deemed to be relevant compared to the rest items in the dataset.<\/p>","DOI":"10.4018\/ijmcmc.2017100102","type":"journal-article","created":{"date-parts":[[2017,11,15]],"date-time":"2017-11-15T10:38:23Z","timestamp":1510742303000},"page":"20-48","source":"Crossref","is-referenced-by-count":8,"title":["Multi-Criteria Recommender Systems"],"prefix":"10.4018","volume":"8","author":[{"given":"Ferdaous","family":"Hdioud","sequence":"first","affiliation":[{"name":"High School of Technology, Lab LTTI, Sidi Mohammed Benabdellah University, Fez, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bouchra","family":"Frikh","sequence":"additional","affiliation":[{"name":"High School of Technology, Lab LTTI, Sidi Mohammed Benabdellah University, Fez, Morocco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brahim","family":"Ouhbi","sequence":"additional","affiliation":[{"name":"High School of Arts and Crafts, Lab. 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