A Two-Stage Calibration Approach for Mitigating Bias and Fairness in Recommender Systems
Author:
Affiliation:
1. University of Sao Paulo, São Carlos, Brazil
Funder
Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3605098.3636092
Reference17 articles.
1. User-centered Evaluation of Popularity Bias in Recommender Systems
2. Connecting user and item perspectives in popularity debiasing for collaborative recommendation
3. Bias and debias in recommender system: A survey and future directions;Chen Jiawei;ACM Transactions on Information Systems,2023
4. Co-training Disentangled Domain Adaptation Network for Leveraging Popularity Bias in Recommenders
5. Diego Corrêa da Silva and Frederico Araújo Durão. 2023. Introducing a framework and a decision protocol to calibrated recommender systems. Applied Intelligence (2023), 1--29.
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