Search results
Results: 5
Number of items: 5
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Honig, S., Oey, E., Wallaard, L., Suttorp, S., & Rus, C. (2025). A reproducibility study of “User-item fairness tradeoffs in recommendations”. Transactions on Machine Learning Research, 2025, Article 4303. https://openreview.net/forum?id=vltzxxhzLU -
Xu, C., Rus, C., Liu, Y., de Jonge, M., Xu, J., & de Rijke, M. (2025). Fairness in information retrieval from an economic perspective. In SIGIR '25: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 13-18, 2025, Padua, Italy (pp. 4126-4129). Association for Computing Machinery. https://doi.org/10.1145/3726302.3731694
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Xu, C., Deng, Z., Rus, C., Ye, X., Liu, Y., Xu, J., Dou, Z., Wen, J.-R., & de Rijke, M. (2025). FairDiverse: A Comprehensive Toolkit for Fairness- and Diversity-aware Information Retrieval. In SIGIR '25: Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 13-18, 2025, Padua, Italy (pp. 3540-3550). Association for Computing Machinery. https://doi.org/10.1145/3726302.3730280
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Rus, C., Poerwawinata, G., Yates, A., & de Rijke, M. (2024). AnnoRank: A Comprehensive Web-Based Framework for Collecting Annotations and Assessing Rankings. In CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management : October, 21-25. 2024, Boise, ID, USA (pp. 5400-5404). Association for Computing Machinery. https://doi.org/10.1145/3627673.3679174
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Rus, C., Yates, A., & de Rijke, M. (2024). A Study of Pre-processing Fairness Intervention Methods for Ranking People. In N. Goharian, N. Tonellotto, Y. He, A. Lipani, G. McDonald, C. Macdonald, & I. Ounis (Eds.), Advances in Information Retrieval: 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24–28, 2024 : proceedings (Vol. IV, pp. 336–350). (Lecture Notes in Computer Science; Vol. 14611). Springer. https://doi.org/10.1007/978-3-031-56066-8_26
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