DeepFair: Deep Learning for Improving Fairness in Recommender Systems

The lack of bias management in Recommender Systems leads to minority groups receiving unfair recommendations. Moreover, the trade-off between equity and precision makes it difficult obtain recommendations that meet both criteria. Here we propose a Deep Learning based Collaborative Filtering algorithm provides with an optimum balance fairness accuracy without knowing demographic information about users. Experimental results show is possible make fair losing significant proportion accuracy.