The Role of Relevance in Fair Ranking
Author:
Affiliation:
1. Massachusetts Institute of Technology, Cambridge, MA, USA
2. University of Michigan, Ann Arbor, MI, USA
3. Max Planck Institute for Security and Privacy, Bochum, Germany
Funder
European Union's Horizon Europe
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3539618.3591933
Reference77 articles.
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2. Qingyao Ai Keping Bi Jiafeng Guo and W Bruce Croft. 2018a. Learning a deep listwise context model for ranking refinement. In ACM SIGIR. 135--144. Qingyao Ai Keping Bi Jiafeng Guo and W Bruce Croft. 2018a. Learning a deep listwise context model for ranking refinement. In ACM SIGIR. 135--144.
3. Qingyao Ai Keping Bi Cheng Luo Jiafeng Guo and W Bruce Croft. 2018b. Unbiased learning to rank with unbiased propensity estimation. In SIGIR. 385--394. Qingyao Ai Keping Bi Cheng Luo Jiafeng Guo and W Bruce Croft. 2018b. Unbiased learning to rank with unbiased propensity estimation. In SIGIR. 385--394.
4. Abolfazl Asudeh HV Jagadish Julia Stoyanovich and Gautam Das. 2019. Designing fair ranking schemes. In SIGMOD. 1259--1276. Abolfazl Asudeh HV Jagadish Julia Stoyanovich and Gautam Das. 2019. Designing fair ranking schemes. In SIGMOD. 1259--1276.
5. Peter Bailey Nick Craswell Ian Soboroff Paul Thomas Arjen P de Vries and Emine Yilmaz. 2008. Relevance assessment: are judges exchangeable and does it matter. In SIGIR. 667--674. Peter Bailey Nick Craswell Ian Soboroff Paul Thomas Arjen P de Vries and Emine Yilmaz. 2008. Relevance assessment: are judges exchangeable and does it matter. In SIGIR. 667--674.
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