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provider perspective

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DataFunSummit
DataFunSummit
Oct 5, 2023 · Artificial Intelligence

Fairness in Recommendation Systems: Consumer and Provider Perspectives

This article examines the fairness of recommendation systems from both consumer and provider viewpoints, discussing sources of bias, definitions of equality and equity, measurement metrics such as CGF and MMF, and proposes causal embedding models to mitigate unfairness while ensuring sustainable system performance.

Machine LearningRecommendation systemscausal inference
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Fairness in Recommendation Systems: Consumer and Provider Perspectives