Balancing Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning

Weiwen Liu, Feng Liu, Ruiming Tang +3

Fairness in recommendation has attracted increasing attention due to bias and discrimination possibly caused by traditional recommenders. In Interactive Recommender Systems (IRS),…