Towards Fair Multi-Stakeholder Recommender Systems

Since recommender systems (“RSs”) are used in multiple domains and applications, issues of possible biases and discrimination have become paramount and present a technical challenge. Indeed, fairness in and for RSs is specific as it does not only concern protected attributes but also encompasses notions of user representativeness and item diversity. In short, RSs require multi-stakeholder fairness. However, RSs are generally built on large (and possibly very sparse) datasets, thus precluding the use of very complex debiasing techniques.