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Recommender systems help users to deal with the information overload problem by producing personalized content according to their interests. Beyond the traditional recommender strategies, there is a growing effort to incorporate users' reviews into the recommendation process, since they provide a rich set of information regarding both items' features and users' preferences. This article proposes a recommender system that uses users' reviews to produce items' representations that are based ondoi:10.1186/s13173-017-0057-8 fatcat:dvznwzljuzfw5ixztj7juihr4a