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Tailored Recommendations

Abstract : Many popular internet platforms use so-called collaborative filtering systems to give personalized recommendations to their users, based on other users who provided similar ratings for some items. We propose a novel approach to such recommendation systems by viewing a recommendation as a way to extend an agent's expressed preferences, which are typically incomplete, through some aggregate of other agents' expressed preferences. These extension and aggregation requirements are expressed by an Acceptance and a Pareto principle, respectively. We characterize the recommendation systems satisfying these two principles and contrast them with collaborative filtering systems, which typically violate the Pareto principle.
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Submitted on : Wednesday, October 21, 2020 - 1:47:41 PM
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Eric Danan, Thibault Gajdos, Jean-Marc Tallon. Tailored Recommendations. Social Choice and Welfare, Springer Verlag, In press, ⟨10.1007/s00355-020-01295-7⟩. ⟨halshs-02973924⟩



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