145 citations · 356 across the 26 of their papers we have counts for
8 papers · 1 filter
The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation
Himan Abdollahpouri, Masoud Mansoury, Robin Burke +1
Recently there has been a growing interest in fairness-aware recommender systems including fairness in providing consistent performance across different users or groups of users. A…
The Evaluation of Rating Systems in Online Free-for-All Games
Arman Dehpanah, Muheeb Faizan Ghori, Jonathan Gemmell +1
Online competitive games have become increasingly popular. To ensure an exciting and competitive environment, these games routinely attempt to match players with similar skill leve…
Feedback Loop and Bias Amplification in Recommender Systems
Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy +2
Recommendation algorithms are known to suffer from popularity bias; a few popular items are recommended frequently while the majority of other items are ignored. These recommendati…
Addressing the Multistakeholder Impact of Popularity Bias in Recommendation Through Calibration
Himan Abdollahpouri, Masoud Mansoury, Robin Burke +1
Popularity bias is a well-known phenomenon in recommender systems: popular items are recommended even more frequently than their popularity would warrant, amplifying long-tail effe…
Using Stable Matching to Optimize the Balance between Accuracy and Diversity in Recommendation
Farzad Eskandanian, Bamshad Mobasher
Increasing aggregate diversity (or catalog coverage) is an important system-level objective in many recommendation domains where it may be desirable to mitigate the popularity bias…
Opportunistic Multi-aspect Fairness through Personalized Re-ranking
Nasim Sonboli, Farzad Eskandanian, Robin Burke +2
As recommender systems have become more widespread and moved into areas with greater social impact, such as employment and housing, researchers have begun to seek ways to ensure fa…