Pdf Interpolating Item And User Fairness In Recommendation Systems

By healtycares On Aug 24, 2025

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BIAS, FAIRNESS, AND MORE IN RECOMMENDER SYSTEMS

BIAS, FAIRNESS, AND MORE IN RECOMMENDER SYSTEMS

BIAS, FAIRNESS, AND MORE IN RECOMMENDER SYSTEMS FAT* 2018: Robin Burke - Balanced Neighborhoods for Multi-sided Fairness in Recommendation RecSys 2020 Tutorial: Counteracting Bias and Increasing Fairness in Search and Recommender Systems Fairness in Recommender Systems: Research Landscape and Future Directions Recommender Systems: Basics, Types, and Design Consideration Women in RecSys: Evaluation Measures of Individual Item Fairness for Recommender Systems Providing Item-side Individual Fairness for Deep Recommender Systems User-oriented Fairness in Recommendation FairCRS: Towards User-oriented Fairness in Conversational Recommendation Systems Tutorial 2: Fairness in Rankings and Recommenders EC'24 Workshop Talk: How Do User and Item Fairness Objectives Affect Recommendation? Data privacy and fairness in recommender systems by Martin Tegner CIIR Talk Series- 4/22/2022: James Caverlee - Interaction Modeling and Fairness in Recommendation Recommender Systems | Walmart Building User Trust in Recommendations via Fairness and Explanations Fairness-Aware Ranking in Search & Recommendation Systems Paper Session 4: A Comparison of Calibrated and Intent-Aware Recommendations - M. Kaya, D. Bridge Paper session 20: Recommendation Systems Fairness in Recommendation Ranking through Pairwise Comparisons Fairness and Diversity in Social-Based Recommender Systems

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