DeepFair: Deep Learning for Improving Fairness in Recommender Systems

Understand

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 to obtain recommendations that meet both criteria.
• Here we propose a Deep Learning based Collaborative Filtering algorithm that provides recommendations with an optimum balance between fairness and accuracy without knowing demographic information about the users.
• Experimental results show that it is possible to make fair recommendations without losing a significant proportion of accuracy.