Multistakeholder recommendation: Survey and research directions

Author:

Abdollahpouri Himan,Adomavicius Gediminas,Burke RobinORCID,Guy Ido,Jannach Dietmar,Kamishima Toshihiro,Krasnodebski Jan,Pizzato Luiz

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Human-Computer Interaction,Education

Reference122 articles.

1. Abdollahpouri, H., Burke, R.: Multi-stakeholder recommendation and its connection to multi-sided fairness. In: Workshop on Recommendation in Multi-stakeholder Environments (RMSE’19), in Conjunction with the 13th ACM Conference on Recommender Systems, RecSys’19 (2019)

2. Abdollahpouri, H., Burke, R., Mobasher, B.: Controlling popularity bias in learning to rank recommendation. In: Proceedings of the 11th ACM Conference on Recommender Systems (2017a)

3. Abdollahpouri, H., Burke, R., Mobasher, B.: Recommender systems as multistakeholder environments. In: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization (UMAP’17) (2017b)

4. Abdollahpouri, H., Burke, R., Mobasher, B..: Managing popularity bias in recommender systems with personalized re-ranking. In: The Thirty-Second International Flairs Conference (2019a)

5. Abdollahpouri, H., Mansoury, M., Burke, R., Mobasher, B.: The unfairness of popularity bias in recommendation. In: RecSys Workshop on Recommendation in Multi-stakeholder Environments (2019b)

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