Long-term Dynamics of Fairness Intervention in Connection Recommender Systems-Reference-Cited by-同舟云学术

Long-term Dynamics of Fairness Intervention in Connection Recommender Systems

Published:2022-07-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society
language:
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Author:

Akpinar Nil-Jana¹,DiCiccio Cyrus²,Nandy Preetam³,Basu Kinjal³

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA, USA

2. Work done at LinkedIn, Sunnyvale, CA, USA

3. LinkedIn, Sunnyvale, CA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3514094.3534173

Reference67 articles.

1. Himan Abdollahpouri , Gediminas Adomavicius , Robin Burke , Ido Guy , Dietmar Jannach , Toshihiro Kamishima , Jan Krasnodebski , and Luiz Pizzato . 2019 a. Beyond Personalization: Research Directions in Multistakeholder Recommendation. arXiv preprint ( 2019 ). https://arxiv.org/abs/1905.01986 Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, and Luiz Pizzato. 2019 a. Beyond Personalization: Research Directions in Multistakeholder Recommendation. arXiv preprint (2019). https://arxiv.org/abs/1905.01986

2. Himan Abdollahpouri and Masoud Mansoury . 2020. Multi-sided Exposure Bias in Recommendation. arXiv preprint ( 2020 ). https://arxiv.org/abs/2006.15772 Himan Abdollahpouri and Masoud Mansoury. 2020. Multi-sided Exposure Bias in Recommendation. arXiv preprint (2020). https://arxiv.org/abs/2006.15772

3. Himan Abdollahpouri , Masoud Mansoury , Robin Burke , and Bamshad Mobasher . 2019 b. The Unfairness of Popularity Bias in Recommendation. arXiv preprint ( 2019 ). https://arxiv.org/abs/1907.13286 Himan Abdollahpouri, Masoud Mansoury, Robin Burke, and Bamshad Mobasher. 2019 b. The Unfairness of Popularity Bias in Recommendation. arXiv preprint (2019). https://arxiv.org/abs/1907.13286

4. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions

5. Online Parameter Selection for Web-based Ranking Problems

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