| Controlling popularity bias in learning-to-rank recommendation H Abdollahpouri, R Burke, B Mobasher Proceedings of the eleventh ACM conference on recommender systems, 42-46, 2017 | 489 | 2017 |
| Managing Popularity Bias in Recommender Systems with Personalized Re-ranking H Abdollahpouri, R Burke, B Mobasher The 32nd International FLAIRS Conference in Cooperation with AAAI, 2019 | 366 | 2019 |
| Multistakeholder recommendation: Survey and research directions H Abdollahpouri, G Adomavicius, R Burke, I Guy, D Jannach, ... User Modeling and User-Adapted Interaction, 1-32, 2020 | 321 | 2020 |
| The Unfairness of Popularity Bias in Recommendation H Abdollahpouri, M Mansoury, R Burke, B Mobasher Proceedings of the RMSE workshop at the ACM Recsys 2019, 2019 | 307 | 2019 |
| 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 | 296 | 2020 |
| The connection between popularity bias, calibration, and fairness in recommendation H Abdollahpouri, M Mansoury, R Burke, B Mobasher Fourteenth ACM Conference on Recommender Systems, 726-731, 2020 | 161 | 2020 |
| User-centered Evaluation of Popularity Bias in Recommender Systems H Abdollahpouri, M Mansoury, R Burke, B Mobasher, E Malthouse 29th ACM Conference on User Modeling, Adaptation and Personalization, 2021 | 134 | 2021 |
| Popularity Bias in Ranking and Recommendation H Abdollahpouri Conference on AI, Ethic and Society (AIES'19), 2019 | 124 | 2019 |
| Multi-stakeholder recommendation and its connection to multi-sided fairness H Abdollahpouri, R Burke arXiv preprint arXiv:1907.13158, 2019 | 111 | 2019 |
| Recommender systems as multistakeholder environments H Abdollahpouri, R Burke, B Mobasher Proceedings of the 25th Conference on User Modeling, Adaptation and …, 2017 | 99 | 2017 |
| Multi-sided Exposure Bias in Recommendation H Abdollahpouri, M Mansoury ACM KDD Workshop on Industrial Recommendation, 2020 | 98 | 2020 |
| Towards multi-stakeholder utility evaluation of recommender systems. RD Burke, H Abdollahpouri, B Mobasher, T Gupta UMAP (Extended Proceedings) 750, 2016 | 98 | 2016 |
| 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 | 76 | 2020 |
| Beyond personalization: Research directions in multistakeholder recommendation H Abdollahpouri, G Adomavicius, R Burke, I Guy, D Jannach, ... arXiv preprint arXiv:1905.01986, 2019 | 71 | 2019 |
| 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 | 53 | 2021 |
| Multistakeholder recommender systems H Abdollahpouri, R Burke Recommender systems handbook, 647-677, 2021 | 42 | 2021 |
| Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems M Mansoury, H Abdollahpouri, J Smith, A Dehpanah, M Pechenizkiy, ... 33rd FLAIRS Conference in Cooperation with AAAI (2020), 2020 | 39 | 2020 |
| Popularity Bias in Recommendation: A Multi-stakeholder Perspective H Abdollahpouri PhD Dissertation, University of Colorado Boulder, 2020 | 38 | 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 | 38 | 2019 |
| Toward the Next Generation of News Recommender Systems H Abdollahpouri, E Malthouse, J Konstan, B Mobasher, J Gilbert Workshop on News Recommendation and Intelligence at WWW’21, 2021 | 35 | 2021 |
Robin BurkeUniversity of Colorado, Boulder確認したメール アドレス: colorado.edu