A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers
June 04, 2018 Β· Declared Dead Β· π Neural Information Processing Systems
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Authors
Omer Ben-Porat, Moshe Tennenholtz
arXiv ID
1806.00955
Category
cs.GT: Game Theory
Cross-listed
cs.IR
Citations
82
Venue
Neural Information Processing Systems
Last Checked
5 months ago
Abstract
We introduce a game-theoretic approach to the study of recommendation systems with strategic content providers. Such systems should be fair and stable. Showing that traditional approaches fail to satisfy these requirements, we propose the Shapley mediator. We show that the Shapley mediator fulfills the fairness and stability requirements, runs in linear time, and is the only economically efficient mechanism satisfying these properties.
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