DataFunSummit
May 1, 2024 · Artificial Intelligence
Causal Solutions for Recommendation System Bias and Practical Applications
This article presents causal inference–based methods to address bias in recommendation systems, covering the transformation of recommendation problems into causal problems, selection bias mitigation through double‑robust and multi‑robust learning, individual treatment effect estimation, and a case study on attention bias in music recommendation.
bias mitigationcausal inferencedouble robust learning
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