Himan Abdollahpouri

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Robin BurkeUniversity of Colorado, BoulderVerified email at colorado.edu
Bamshad MobasherSchool of Computing, DePaul UniversityVerified email at cs.depaul.edu
Masoud MansouryPhD Candidate, Eindhoven University of TechnologyVerified email at tue.nl
Jan KrasnodebskiSenior Director Data ScienceVerified email at expediagroup.com
Ido GuyResearch Director, eBayVerified email at ebay.com
Gediminas AdomaviciusProfessor of Information and Decision Sciences, University of MinnesotaVerified email at umn.edu
Luiz Augusto PizzatoCommonwealth Bank of AustraliaVerified email at acm.org
Mykola PechenizkiyEindhoven University of TechnologyVerified email at tue.nl
Dietmar JannachUniversity of Klagenfurt, Austria; University of Bergen, NorwayVerified email at aau.at
Toshihiro KamishimaNational Institute of Advanced Industrial Science and Technology (AIST)Verified email at kamishima.net
Edward C MalthouseNorthwestern University: integrated marketing communications, industrial engineering and mgmt sciVerified email at northwestern.edu
Alireza AbdollahpouriDept. of Computer, Faculty of Engineering, University of Kurdistan, Sanandaj, IranVerified email at uok.ac.ir
Yongfeng ZhangRutgers University, Department of Computer ScienceVerified email at rutgers.edu
Arman DehpanahPhD Candidate, DePaul University, Chicago, USAVerified email at depaul.edu
Jessie J. SmithPhD Student, University of Colorado BoulderVerified email at colorado.edu
Joseph A. KonstanUniversity of MinnesotaVerified email at umn.edu
Steven D. EssingerDrexel UniversityVerified email at drexel.edu
Khanh-Phuong (KP) Thai, PhDUniversity of California Los AngelesVerified email at ucla.edu
Yi ZhangProfessor of Engineering, University of California, Santa CruzVerified email at soe.ucsc.edu

Himan Abdollahpouri

Northwestern University

Verified email at northwestern.edu

Recommender Systems Data Mining User Modeling Personalization Fairness


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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	106	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	52	2019
Recommender systems as multistakeholder environments H Abdollahpouri, R Burke, B Mobasher Proceedings of the 25th Conference on User Modeling, Adaptation and …, 2017	45	2017
Towards Multi-Stakeholder Utility Evaluation of Recommender Systems. RD Burke, H Abdollahpouri, B Mobasher, T Gupta UMAP (Extended Proceedings), 2016	43	2016
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	35	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	31	2019
Beyond personalization: Research directions in multistakeholder recommendation H Abdollahpouri, G Adomavicius, R Burke, I Guy, D Jannach, ... arXiv preprint arXiv:1905.01986, 2019	28	2019
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	19	2019
Educational recommendation with multiple stakeholders R Burke, H Abdollahpouri 2016 IEEE/WIC/ACM International Conference on Web Intelligence Workshops …, 2016	17	2016
Patterns of Multistakeholder Recommendation R Burke, H Abdollahpouri VAMS@RecSys'17 workshop on value-aware and multistakeholder recommendation, 2017	11	2017
Popularity Bias in Ranking and Recommendation H Abdollahpouri Conference on AI, Ethic and Society (AIES'19), 2019	10	2019
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	9	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	8	2019
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	8	2013
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	7	2020
Multi-sided Exposure Bias in Recommendation H Abdollahpouri, M Mansoury ACM KDD Workshop on Industrial Recommendation, 2020	7	2020
Multiple stakeholders in music recommender systems H Abdollahpouri, S Essinger VAMS@RecSys'17 workshop on value-aware and multistakeholder recommendation, 2017	7	2017
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	6	2020
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	6	2017
Towards Effective Exploration/Exploitation in Sequential Music Recommendation H Abdollahpouri, S Essinger RecSys posters, 2017	5	2017

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