Advances in Bias-aware Recommendation on the Web
Author:
Affiliation:
1. EURECAT - Centre Tecnológic de Catalunya, Barcelona, Spain
2. École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Italy
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3437963.3441665
Reference24 articles.
1. Multistakeholder recommendation: Survey and research directions
2. Statistical biases in Information Retrieval metrics for recommender systems
3. Fairness-Aware Machine Learning
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2. Recommender Systems: Techniques, Effects, and Measures Toward Pluralism and Fairness;Introduction to Digital Humanism;2023-12-21
3. Looks Can Be Deceiving: Linking User-Item Interactions and User’s Propensity Towards Multi-Objective Recommendations;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14
4. Debiaser for Multiple Variables to enhance fairness in classification tasks;Information Processing & Management;2023-03
5. Bias Assessment Approaches for Addressing User-Centered Fairness in GNN-Based Recommender Systems;Information;2023-02-17
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