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Multi-Stakeholder Recommendation: Applications and Challenges

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arxiv 1707.08913 v1 pith:4C6EQEQF submitted 2017-07-27 cs.IR

classification cs.IR
keywords recommendationsmulti-stakeholderapplicationschallengesrecommendationrecommendersystemsusers
verification ladder T0 review T1 audit T2 compute T3 formal
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Recommender systems have been successfully applied to assist decision making by producing a list of item recommendations tailored to user preferences. Traditional recommender systems only focus on optimizing the utility of the end users who are the receiver of the recommendations. By contrast, multi-stakeholder recommendation attempts to generate recommendations that satisfy the needs of both the end users and other parties or stakeholders. This paper provides an overview and discussion about the multi-stakeholder recommendations from the perspective of practical applications, available data sets, corresponding research challenges and potential solutions.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Equity by Design? On the Trade-Offs in Fairness-Driven Recommendation in Heterogeneous Two-Sided Markets

    cs.GT 2026-02 conditional novelty 6.0 of 10

    The 'free fairness' result for producer constraints vanishes for multi-item recommendations; a CVaR group-fairness objective and business constraints can be added with moderate trade-offs.

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