Tailored recommendations

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 exte...

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Bibliographic Details
Published in:Social choice and welfare 2023, Vol.60 (1-2), p.15-34
Main Authors: Danan, Eric, Gajdos, Thibault, Tallon, Jean-Marc
Format: Article
Language:English
Subjects:
Collaboration
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
Expected utility
Filtering systems
Game Theory
Humanities and Social Sciences
International Political Economy
Internet
Original Paper
Preferences
Principles
Public Finance
Ratings & rankings
Recommender systems
Social and Behav. Sciences
Social Policy
Citations: Items that this one cites
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Summary: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.
ISSN:0176-1714
1432-217X
DOI:10.1007/s00355-020-01295-7