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Found 2 papers, 1 papers with code
Beyond Static Calibration: The Impact of User Preference Dynamics on Calibrated Recommendation
Calibration in recommender systems is an important performance criterion that ensures consistency between the distribution of user preference categories and that of recommendations generated by the system.
Crank up the volume: preference bias amplification in collaborative recommendation
Recommender systems are personalized: we expect the results given to a particular user to reflect that user's preferences.
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