The paper presents a recommender system that permits to manage user preferences using linguistic criteria and, after collecting information about selections made by the user, it performs an unsupervised adaptation of the user profile. It has been implemented as a Web application and designed in a generic way so that it can be applied to any decision making problem. It includes two separate modules: a module to rate and rank all alternatives received by the system according to the current interests of the user, and a module to adapt the current user profile in an unsupervised fashion collecting implicit information about the user interaction with the system. The paper presents some preliminary results and discusses the performance of the adaptation algorithm.