Abstract
In research practice, recommender systems are typically evaluated on their ability to provide items that satisfy the needs and interests of the end user. However, in many recommendation domains, the user for whom recommendations are generated is not the only stakeholder in the recommendation outcome. For example, fairness and balance across stakeholders is important in some recommendation applications; achieving a goal such as promoting new sellers in a marketplace might be important in others. Such multistakeholder environments present unique challenges for recommender system design and evaluation, and these challenges were the focus of this workshop.
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CITATION STYLE
Burke, R., Abdollahpouri, H., Malthouse, E. C., Thai, K. P., & Zhang, Y. (2019). Recommendation in multistakeholder environments. In RecSys 2019 - 13th ACM Conference on Recommender Systems (pp. 566–567). Association for Computing Machinery, Inc. https://doi.org/10.1145/3298689.3346973
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