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Fairness and Transparency in Recommendation: The Users' Perspective

, , , , and . Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, page 274-279. ACM, (June 2021)How to explain recommendations that are generated from fairness prospect?.
DOI: 10.1145/3450613.3456835

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Opportunistic Multi-aspect Fairness through Personalized Re-ranking., , , , and . UMAP, page 239-247. ACM, (2020)librec-auto: A Tool for Recommender Systems Experimentation., , , , , , , and . CIKM, page 4584-4593. ACM, (2021)FAccTRec 2022: The 5th Workshop on Responsible Recommendation., , , , and . RecSys, page 686-687. ACM, (2022)Crank up the Volume: Preference Bias Amplification in Collaborative Recommendation., , , and . RMSE@RecSys, volume 2440 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)Calibration in Collaborative Filtering Recommender Systems, , , and . Proceedings of the 31st ACM Conference on Hypertext and Social Media, page 187-206. ACM, (July 2020)FAccTRec 2021: The 4th Workshop on Responsible Recommendation., , , and . RecSys, page 778-779. ACM, (2021)Multi-agent Social Choice for Dynamic Fairness-aware Recommendation., , , , and . UMAP (Adjunct Publication), page 234-244. ACM, (2022)Experimentation with fairness-aware recommendation using librec-auto: hands-on tutorial., , and . FAT*, page 700. ACM, (2020)Localized Fairness in Recommender Systems., and . UMAP (Adjunct Publication), page 295-300. ACM, (2019)Personalized fairness-aware re-ranking for microlending., , , , and . RecSys, page 467-471. ACM, (2019)