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Results: 6
Number of items: 6
  • Open Access
    Huang, J., Oosterhuis, H., Mansoury, M., van Hoof, H., & de Rijke, M. (2024). Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems. In SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 14-18, 2024, Washington, DC, USA (pp. 416-426). Association for Computing Machinery. https://doi.org/10.1145/3626772.3657749
  • Open Access
    Liu, Y., Li, M., Ariannezhad, M., Mansoury, M., Aliannejadi, M., & de Rijke, M. (2024). Measuring Item Fairness in Next Basket Recommendation: A Reproducibility Study. 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. 210-225). (Lecture Notes in Computer Science; Vol. 14611). Springer. https://doi.org/10.1007/978-3-031-56066-8_18
  • Open Access
    Mansoury, M., Mobasher, B., & van Hoof, H. (2024). Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits. In CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management : October, 21-25. 2024, Boise, ID, USA (pp. 1638-1648). Association for Computing Machinery. https://doi.org/10.1145/3627673.3679763
  • Open Access
    Heuss, M., Cohen, D., Mansoury, M., de Rijke, M., & Eickhoff, C. (2023). Predictive Uncertainty-based Bias Mitigation in Ranking. In CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management : October 21-25, 2023, Birmingham, England (pp. 762-772). Association for Computing Machinery. https://doi.org/10.1145/3583780.3615011
  • Open Access
    Abdollahpouri, H., Sahebi, S., Elahi, M., Mansoury, M., Loni, B., Nazari, Z., & Dimakopoulou, M. (2022). MORS 2022: The Second Workshop on Multi-Objective Recommender Systems. In RecSys' 22: Proceedings of the Sixteenth ACM Conference on Recommender Systems : Seattle, WA, USA, September 18-23, 2022 (pp. 658-660). Association for Computing Machinery. https://doi.org/10.1145/3523227.3547410
  • Mansoury, M., Abdollahpouri, H., Pechenizkiy, M., Mobasher, B., & Burke, R. (2022). A graph-based approach for mitigating multi-sided exposure bias in recommender systems. ACM Transactions on Information Systems, 40(2), Article 32. https://doi.org/10.1145/3470948
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