Beyond Personalization: Research Directions in Multistakeholder Recommendation

no code implementations • 1 May 2019 • Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Pizzato

Recommender systems are personalized information access applications; they are ubiquitous in today's online environment, and effective at finding items that meet user needs and tastes.

Fairness Recommendation Systems

A Multi-Objective Learning to re-Rank Approach to Optimize Online Marketplaces for Multiple Stakeholders

no code implementations • 2 Aug 2017 • Phong Nguyen, John Dines, Jan Krasnodebski

However these systems are most often designed to address the objective of one single stakeholder, typically, in online commerce, the consumers whose input and purchasing decisions ultimately determine the success of the recommendation systems.

Recommendation Systems