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• W4247288534 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." @default.
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• W4247288534 date "2020-10-14" @default.
• W4247288534 modified "2023-09-25" @default.
• W4247288534 title "Tailored recommendations" @default.
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• W4247288534 doi "https://doi.org/10.1007/s00355-020-01295-7" @default.
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