145 citations · 356 across the 26 of their papers we have counts for
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cs.IR2024
Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits
Masoud Mansoury, Bamshad Mobasher, Herke van Hoof
Exposure bias is a well-known issue in recommender systems where items and suppliers are not equally represented in the recommendation results. This bias becomes particularly probl…
cs.IR2024
Beyond Static Calibration: The Impact of User Preference Dynamics on Calibrated Recommendation
Kun Lin, Masoud Mansoury, Farzad Eskandanian +2
Calibration in recommender systems is an important performance criterion that ensures consistency between the distribution of user preference categories and that of recommendations…