Himan Abdollahpouri
TitleCited byYear
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
472017
Towards Multi-Stakeholder Utility Evaluation of Recommender Systems.
RD Burke, H Abdollahpouri, B Mobasher, T Gupta
UMAP (Extended Proceedings), 2016
302016
Recommender systems as multistakeholder environments
H Abdollahpouri, R Burke, B Mobasher
Proceedings of the 25th Conference on User Modeling, Adaptation and …, 2017
262017
Educational recommendation with multiple stakeholders
R Burke, H Abdollahpouri
2016 IEEE/WIC/ACM International Conference on Web Intelligence Workshops …, 2016
132016
Beyond Personalization: Research Directions in Multistakeholder Recommendation
H Abdollahpouri, G Adomavicius, R Burke, I Guy, D Jannach, ...
arXiv preprint arXiv:1905.01986, 2019
122019
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
102019
Patterns of Multistakeholder Recommendation
R Burke, H Abdollahpouri
VAMS@RecSys'17 workshop on value-aware and multistakeholder recommendation, 2017
82017
VAMS 2017: Workshop on Value-Aware and Multistakeholder Recommendation
R Burke, G Adomavicius, I Guy, J Krasnodebski, L Pizzato, Y Zhang, ...
Proceedings of the Eleventh ACM Conference on Recommender Systems, 378-379, 2017
62017
Multiple stakeholders in music recommender systems
H Abdollahpouri, S Essinger
VAMS@RecSys'17 workshop on value-aware and multistakeholder recommendation, 2017
62017
An approach for personalization of banking services in multi-channel environment using memory-based collaborative filtering
H Abdollahpouri, A Abdollahpouri
The 5th Conference on Information and Knowledge Technology, 208-213, 2013
52013
Towards Effective Exploration/Exploitation in Sequential Music Recommendation
H Abdollahpouri, S Essinger
RecSys posters, 2017
42017
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
32019
Multi-stakeholder Recommendation and its Connection to Multi-sided Fairness
H Abdollahpouri, R Burke
Proceedings of the RMSE workshop at the ACM Recsys 2019, 2019
32019
Popularity Bias in Ranking and Recommendation
H Abdollahpouri
Conference on AI, Ethic and Society (AIES'19), 2019
32019
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
12019
Incorporating System-Level Objectives into Recommender Systems
H Abdollahpouri
Companion Proceedings of The 2019 World Wide Web Conference, 2-6, 2019
12019
Value-Aware Item Weighting for Long-Tail Recommendation.
H Abdollahpouri, R Burke, B Mobasher
12018
Is Always a Hybrid Recommender System Preferable To Single Techniques?
H Abdollahpouri, A Rahmani, A Abdollahpouri
International Journal of Computer Applications 82 (4), 2013
12013
The Relationship between the Consistency of Users' Ratings and Recommendation Calibration
M Mansoury, H Abdollahpouri, J Rombouts, M Pechenizkiy
arXiv preprint arXiv:1911.00852, 2019
2019
Recommendation in multistakeholder environments
R Burke, H Abdollahpouri, EC Malthouse, KP Thai, Y Zhang
Proceedings of the 13th ACM Conference on Recommender Systems, 566-567, 2019
2019
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Articles 1–20