Contextualized Fairness for Recommender Systems in Premium Scenarios-Reference-Cited by-同舟云学术

Contextualized Fairness for Recommender Systems in Premium Scenarios

Author:

Li Yangkun^ORCID,Hedia Mohamed-Laid,Ma Weizhi,Lu Hongyu,Zhang Min,Liu Yiqun,Ma Shaoping

Publisher

Elsevier BV

Subject

Information Systems and Management,Computer Science Applications,Information Systems,Management Information Systems

Reference40 articles.

1. Recsys challenge 2017: offline and online evaluation;Abel,2017

2. A reductions approach to fair classification;Agarwal,2018

3. Machine bias: there's software used across the country to predict future criminals. And it's biased against blacks;Angwin;ProPublica,2016

4. Fairness in Machine Learning;Barocas,2019

5. Fairness in criminal justice risk assessments: the state of the art;Berk;Sociol. Methods Res.,2018

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