TY - JOUR
T1 - Multistakeholder recommendation
T2 - Survey and research directions
AU - Abdollahpouri, Himan
AU - Adomavicius, Gediminas
AU - Burke, Robin
AU - Guy, Ido
AU - Jannach, Dietmar
AU - Kamishima, Toshihiro
AU - Krasnodebski, Jan
AU - Pizzato, Luiz
N1 - Publisher Copyright:
© 2020, Springer Nature B.V.
PY - 2020/3/1
Y1 - 2020/3/1
N2 - Recommender systems provide personalized information access to users of Internet services from social networks to e-commerce to media and entertainment. As is appropriate for research in a field with a focus on personalization, academic studies of recommender systems have largely concentrated on optimizing for user experience when designing, implementing and evaluating their algorithms and systems. However, this concentration on the user has meant that the field has lacked a systematic exploration of other aspects of recommender system outcomes. A user-centric approach limits the ability to incorporate system objectives, such as fairness, balance, and profitability, and obscures concerns that might come from other stakeholders, such as the providers or sellers of items being recommended. Multistakeholder recommendation has emerged as a unifying framework for describing and understanding recommendation settings where the end user is not the sole focus. This article outlines the multistakeholder perspective on recommendation, highlighting example research areas and discussing important issues, open questions, and prospective research directions.
AB - Recommender systems provide personalized information access to users of Internet services from social networks to e-commerce to media and entertainment. As is appropriate for research in a field with a focus on personalization, academic studies of recommender systems have largely concentrated on optimizing for user experience when designing, implementing and evaluating their algorithms and systems. However, this concentration on the user has meant that the field has lacked a systematic exploration of other aspects of recommender system outcomes. A user-centric approach limits the ability to incorporate system objectives, such as fairness, balance, and profitability, and obscures concerns that might come from other stakeholders, such as the providers or sellers of items being recommended. Multistakeholder recommendation has emerged as a unifying framework for describing and understanding recommendation settings where the end user is not the sole focus. This article outlines the multistakeholder perspective on recommendation, highlighting example research areas and discussing important issues, open questions, and prospective research directions.
UR - http://www.scopus.com/inward/record.url?scp=85077690286&partnerID=8YFLogxK
U2 - 10.1007/s11257-019-09256-1
DO - 10.1007/s11257-019-09256-1
M3 - Article
AN - SCOPUS:85077690286
SN - 0924-1868
VL - 30
SP - 127
EP - 158
JO - User Modeling and User-Adapted Interaction
JF - User Modeling and User-Adapted Interaction
IS - 1
ER -