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Unfair Exposure of Artists in Music Recommendation
[article]
2020
arXiv
pre-print
Fairness in machine learning has been studied by many researchers. In particular, fairness in recommender systems has been investigated to ensure the recommendations meet certain criteria with respect to certain sensitive features such as race, gender etc. However, often recommender systems are multi-stakeholder environments in which the fairness towards all stakeholders should be taken care of. It is well-known that the recommendation algorithms suffer from popularity bias; few popular items
arXiv:2003.11634v1
fatcat:z6febc35bvezbece4da4nvj4oq