  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.
