145 citations · 456 across the 34 of their papers we have counts for
5 papers · 1 filter
The Relationship between the Consistency of Users' Ratings and Recommendation Calibration
Masoud Mansoury, Himan Abdollahpouri, Joris Rombouts +1
Fairness in recommender systems has recently received attention from researchers. Unfair recommendations have negative impact on the effectiveness of recommender systems as it may…
The Impact of Popularity Bias on Fairness and Calibration 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.…
Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison
Masoud Mansoury, Bamshad Mobasher, Robin Burke +1
Research on fairness in machine learning has been recently extended to recommender systems. One of the factors that may impact fairness is bias disparity, the degree to which a gro…
Flatter is better: Percentile Transformations for Recommender Systems
Masoud Mansoury, Robin Burke, Bamshad Mobasher
It is well known that explicit user ratings in recommender systems are biased towards high ratings, and that users differ significantly in their usage of the rating scale. Implemen…
The Unfairness of Popularity Bias in Recommendation
Himan Abdollahpouri, Masoud Mansoury, Robin Burke +1
Recommender systems are known to suffer from the popularity bias problem: popular (i.e. frequently rated) items get a lot of exposure while less popular ones are under-represented…