Multi-stakeholder Recommendation and its Connection to Multi-sided Fairness
This work addresses a gap in organizing and understanding multi-stakeholder recommendation for researchers, but it is incremental as it builds on existing areas like reciprocal and group recommendation.
The paper tackles the lack of a detailed taxonomy for multi-stakeholder recommender systems and explores their connection to fairness concerns, providing definitions and discussions to clarify these relationships.
There is growing research interest in recommendation as a multi-stakeholder problem, one where the interests of multiple parties should be taken into account. This category subsumes some existing well-established areas of recommendation research including reciprocal and group recommendation, but a detailed taxonomy of different classes of multi-stakeholder recommender systems is still lacking. Fairness-aware recommendation has also grown as a research area, but its close connection with multi-stakeholder recommendation is not always recognized. In this paper, we define the most commonly observed classes of multi-stakeholder recommender systems and discuss how different fairness concerns may come into play in such systems.