Rectifying Unfairness in Recommendation Feedback Loop-Reference-Cited by-同舟云学术

Rectifying Unfairness in Recommendation Feedback Loop

Published:2023-07-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Yang Mengyue¹^ORCID,Wang Jun¹^ORCID,Ton Jean-Francois²^ORCID

Affiliation:

1. University College London, London, United Kingdom

2. ByteDance Research, London, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539618.3591754

Reference47 articles.

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2. Unbiased Learning to Rank with Unbiased Propensity Estimation

3. Fairness in Recommendation Ranking through Pairwise Comparisons

4. Jiawei Chen , Hande Dong , Yang Qiu , Xiangnan He , Xin Xin , Liang Chen , Guli Lin , and Keping Yang . 2021. AutoDebias: Learning to Debias for Recommendation. arXiv preprint arXiv:2105.04170 ( 2021 ). Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, and Keping Yang. 2021. AutoDebias: Learning to Debias for Recommendation. arXiv preprint arXiv:2105.04170 (2021).

5. Jiawei Chen , Hande Dong , XiangWang, Fuli Feng , MengWang, and Xiangnan He. 2020. Bias and Debias in Recommender System: A Survey and Future Directions. CoRR abs/2010.03240 ( 2020 ). arXiv:2010.03240 Jiawei Chen, Hande Dong, XiangWang, Fuli Feng, MengWang, and Xiangnan He. 2020. Bias and Debias in Recommender System: A Survey and Future Directions. CoRR abs/2010.03240 (2020). arXiv:2010.03240

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