Fairness in Graph-based Recommendation: Methods Overview
Author:
Affiliation:
1. University of Zagreb,Faculty of Electrical Engineering and Computing,Zagreb,Croatia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10569139/10569147/10569148.pdf?arnumber=10569148
Reference26 articles.
1. The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation
2. Towards a unified framework for fair and stable graph representation learning;Agarwal;Uncertainty in Artificial Intelligence,2021
3. Fairness in Recommendation Ranking through Pairwise Comparisons
4. Compositional fairness constraints for graph embeddings;Bose
5. DeBayes: a bayesian method for debiasing network embeddings;Buyl
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