1 Result(s)

Chapter and Conference Paper

Balancing Between Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning

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

Weiwen Liu, Feng Liu, Ruiming Tang, Ben Liao… in Advances in Knowledge Discovery and Data M… (2020)