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There is growing research interest in recommendation as a multi-stakeholder problem, one where the interests of multiple parties should be taken into account.
A hybrid approach for movie recommendation
George Lekakos and Petros Caravelas. 2008 · 2008
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Music recommendation
Oscar Celma. 2010 · 2010
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Group recommender systems: Combining individual models
Judith Masthoff. 2011 · 2011
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Machine learned job recommendation. In Proceedings of the fifth ACM Conference on Recommender Systems . ACM, 325–328
Ioannis Paparrizos, B Barla Cambazoglu, and Aristides Gionis. 2011 · 2011
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Improving recommendation for long-tail queries via templates. In Proceedings of the 20th international conference on World wide web . ACM, 47–56
Idan Szpektor, Aristides Gionis, and Yoelle Maarek. 2011 · 2011
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Reciprocal recommendation algorithm for the field of recruitment
Hongtao Yu, Chaoran Liu, and Fuzhi Zhang. 2011 · 2011
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Enhancement of the Neutrality in Recommendation.. In Decisions@ RecSys . 8–14
Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, and Jun Sakuma. 2012 · 2012
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Movie recommender system for profit maximization. In Proceedings of the 7th ACM conference on Recommender systems . ACM, 121–128
Amos Azaria, Avinatan Hassidim, Sarit Kraus, Adi Eshkol, Ofer Weintraub, and Irit Netanely. 2013 · 2013
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Fairness-Aware Loan Recommendation for Microfinance Services. ACM Press, 1–4
Eric L. Lee, Jing-Kai Lou, Wei-Ming Chen, Yen-Chi Chen, Shou-De Lin, Yen-Sheng Chiang, and Kuan-Ta Chen. 2014 · 2014
Cited alongside, same era.
Optimal real-time bidding for display advertising. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining . ACM, 1077–1086
Weinan Zhang, Shuai Yuan, and Jun Wang. 2014 · 2014
Cited alongside, same era.
Reciprocal Recommendation System for Online Dating. In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 . ACM, 234–241
Peng Xia, Benyuan Liu, Yizhou Sun, and Cindy Chen. 2015 · 2015
Cited alongside, same era.
Towards Multi-Stakeholder Utility Evaluation of Recommender Systems. In Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems, UMAP 2016
Robin D. Burke, Himan Abdollahpouri, Bamshad Mobasher, and Trinadh Gupta. 2016 · 2016
Cited alongside, same era.
Fairness-aware group recommendation with pareto-efficiency. In Proceedings of the Eleventh ACM Conference on Recommender Systems . ACM, 107–115
Lin Xiao, Zhang Min, Zhang Yongfeng, Gu Zhaoquan, Liu Yiqun, and Ma Shaoping. 2017 · 2017
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Beyond parity: Fairness objectives for collaborative filtering. In Advances in Neural Information Processing Systems . 2921–2930
Sirui Yao and Bert Huang. 2017 · 2017
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Group recommender systems: An introduction
Alexander Felfernig, Ludovico Boratto, Martin Stettinger, and Marko Tkalčič. 2018 · 2018
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Towards a fair marketplace: Counterfactual evaluation of the trade-off between relevance, fairness & satisfaction in recommendation systems. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management . ACM, 2243–2251
Rishabh Mehrotra, James McInerney, Hugues Bouchard, Mounia Lalmas, and Fernando Diaz. 2018 · 2018
Later among the works it cites.
Beyond Personalization: Research Directions in Multistakeholder Recommendation
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Recommender systems as multi-stakeholder environments. In Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization (UMAP2017) . ACM
Himan Abdollahpouri, Robin Burke, and Bamshad Mobasher. 2017 · 2017
Cited alongside, same era.
VAMS 2017: Workshop on Value-Aware and Multistakeholder Recommendation. In Proceedings of the Eleventh ACM Conference on Recommender Systems . ACM, 378–379
Robin Burke, Gediminas Adomavicius, Ido Guy, Jan Krasnodebski, Luiz Pizzato, Yi Zhang, and Himan Abdollahpouri. 2017a · 2017
Cited alongside, same era.
Price and Profit Awareness in Recommender Systems. In Proceedings of the ACM RecSys 2017 Workshop on Value-Aware and Multi-Stakeholder Recommendation . Como, Italy
Dietmar Jannach and Gediminas Adomavicius. 2017 · 2017
Cited alongside, same era.
Managing Popularity Bias in Recommender Systems with Personalized Re-ranking.. In Florida AI Research Symposium (FLAIRS) . ACM, To appear
Himan Abdollahpouri, Robin Burke, and Bamshad Mobasher. 2019b
Cited in the paper.
Balanced Neighborhoods for Fairness-aware Collaborative Recommendation. In Workshop on Responsible Recommendation (FATRec)
Robin Burke, Nasim Sonboli, Masoud Mansoury, and Aldo Ordoñez-Gauger. 2017b
Cited in the paper.
RECON: a reciprocal recommender for online dating. In Proceedings of the fourth ACM conference on Recommender systems . ACM, 207–214
Luiz Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, and Judy Kay. 2010a
Cited in the paper.
RECON: a reciprocal recommender for online dating. In Proceedings of the fourth ACM conference on Recommender systems . ACM, 207–214
Luiz Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, and Judy Kay. 2010b
Cited in the paper.
Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, and Luiz Pizzato. 2019a · 2019
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Value-aware Recommendation based on Reinforced Profit Maximization in E-commerce Systems
Changhua Pei, Xinru Yang, Qing Cui, Xiao Lin, Fei Sun, Peng Jiang, Wenwu Ou, and Yongfeng Zhang. 2019 · 2019
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Yong Zheng, Nastaran Ghane, and Milad Sabouri. 2019 · 2019
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