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Title: Tecnologías que mejoran la privacidad en los sistemas de recomendación
Author: Gil Mayo, Francisco
Director: Parra Arnau, Javier
Tutor: Rodríguez Velázquez, Juan Alberto
Others: Universitat Oberta de Catalunya
Keywords: privacy enhancements
recommendation systems
rating perturbative mechanisms
Issue Date: 15-Jun-2017
Publisher: Universitat Oberta de Catalunya
Abstract: The development of Internet, mobiles and the appearance of numerous applications are quickly changing our society. Many applications have personalized recommendation systems to analyze the preferences of each customer and to predict the interest they will have for a particular item. There are two usual strategies: "forgery" where we change the items rating for user doesn't show his real interests and "suppression" where the items rating is eliminated. The purpose of this paper is to evaluate the impact of these two strategies on real utilities of a recommendation system such as MAE and RMSE.
Language: Spanish
Appears in Collections:Bachelor thesis, research projects, etc.

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