Recommendation in multistakeholder environments

Robin Burke, Himan Abdollahpouri, Edward C. Malthouse, K. P. Thai, Yongfeng Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationRecSys 2019 - 13th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Number of pages2
ISBN (Electronic)9781450362436
StatePublished - Sep 10 2019
Event13th ACM Conference on Recommender Systems, RecSys 2019 - Copenhagen, Denmark
Duration: Sep 16 2019Sep 20 2019

Publication series

NameRecSys 2019 - 13th ACM Conference on Recommender Systems


Conference13th ACM Conference on Recommender Systems, RecSys 2019

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Computer Science Applications


  • Bias
  • Discrimination
  • E-commerce
  • Fairness
  • Multistakeholder recommendation


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