| The Unfairness of Popularity Bias in Recommendation H Abdollahpouri, M Mansoury, R Burke, B Mobasher RecSys Workshop on Recommendation in Multistakeholder Environments (RMSE), 2019 | 215 | 2019 |
| Balanced neighborhoods for fairness-aware collaborative recommendation R Burke, N Sonboli, M Mansoury, A Ordoñez-Gauger RecSys Worshop on Fairness, Accountability, and Transparency in Recommender …, 2017 | 210* | 2017 |
| Feedback Loop and Bias Amplification in Recommender Systems M Mansoury, H Abdollahpouri, M Pechenizkiy, B Mobasher, R Burke 29th ACM International Conference on Information and Knowledge Management …, 2020 | 185 | 2020 |
| The connection between popularity bias, calibration, and fairness in recommendation H Abdollahpouri, M Mansoury, R Burke, B Mobasher Proceedings of the 14th ACM Conference on Recommender Systems, 726-731, 2020 | 97 | 2020 |
| User-centered evaluation of popularity bias in recommender systems H Abdollahpouri, M Mansoury, R Burke, B Mobasher, E Malthouse Proceedings of the 29th ACM Conference on User Modeling, Adaptation and …, 2021 | 72 | 2021 |
| Multi-sided Exposure Bias in Recommendation H Abdollahpouri, M Mansoury ACM KDD Workshop on Industrial Recommendation Systems 2020, 2020 | 71 | 2020 |
| Multi-sided exposure bias in recommendation A Himan, M Masoud In ACM KDD’20 Workshop on Industrial Recommendation Systems, 2020 | 71* | 2020 |
| FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems M Mansoury, H Abdollahpouri, M Pechenizkiy, B Mobasher, R Burke 28th Conference on User Modeling, Adaptation and Personalization (UMAP 2020), 2020 | 52 | 2020 |
| A graph-based approach for mitigating multi-sided exposure bias in recommender systems M Mansoury, H Abdollahpouri, M Pechenizkiy, B Mobasher, R Burke ACM Transactions on Information Systems (TOIS) 40 (2), 1-31, 2021 | 31 | 2021 |
| Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison M Mansoury, B Mobasher, R Burke, M Pechenizkiy RecSys Workshop on Recommendation in Multistakeholder Environments (RMSE), 2019 | 29 | 2019 |
| Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems M Mansoury, H Abdollahpouri, J Smith, A Dehpanah, M Pechenizkiy, ... The 33nd International FLAIRS Conference in Cooperation with AAAI, 2020 | 28 | 2020 |
| The impact of popularity bias on fairness and calibration in recommendation H Abdollahpouri, M Mansoury, R Burke, B Mobasher arXiv preprint arXiv:1910.05755, 2019 | 25 | 2019 |
| Automating recommender systems experimentation with librec-auto M Mansoury, R Burke, A Ordonez-Gauger, X Sepulveda Proceedings of the 12th ACM Conference on Recommender Systems, 500-501, 2018 | 20 | 2018 |
| Beyond algorithmic fairness in recommender systems M Elahi, H Abdollahpouri, M Mansoury, H Torkamaan Adjunct proceedings of the 29th ACM conference on user modeling, adaptation …, 2021 | 18 | 2021 |
| Fairness-aware recommendation in multi-sided platforms M Mansoury Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 14 | 2021 |
| Addressing the multistakeholder impact of popularity bias in recommendation through calibration H Abdollahpouri, M Mansoury, R Burke, B Mobasher arXiv preprint arXiv:2007.12230, 2020 | 14* | 2020 |
| Algorithm selection with librec-auto M Mansoury, R Burke Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in …, 2019 | 14 | 2019 |
| Improving recommender systems’ performance on cold-start users and controversial items by a new similarity model M Mansoury, M Shajari International Journal of Web Information Systems 12 (2), 126-149, 2016 | 12 | 2016 |
| Unfair exposure of artists in music recommendation H Abdollahpouri, R Burke, M Mansoury arXiv preprint arXiv:2003.11634, 2020 | 10* | 2020 |
| Flatter is better: percentile transformations for recommender systems M Mansoury, R Burke, B Mobasher ACM Transactions on Intelligent Systems and Technology (TIST) 12 (2), 1-16, 2021 | 9 | 2021 |
Himan AbdollahpouriResearch Scientist at SpotifyVerified email at spotify.com
