A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers

被引：0

作者：

Ben-Porat, Omer ^{[1
]}

Tennenholtz, Moshe ^{[1
]}

机构：

[1] Technion Israel Inst Technol, IL-32000 Haifa, Israel

来源：

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018) | 2018年 / 31卷

基金：

欧洲研究理事会;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页数：11

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