Recommender Systems

This paper investigates the issue of fairness for cyber recommendation systems by adopting a multi-sided concept so that multiple individuals are taken into account regarding multiple outcomes to establish user trust in cyberspace. As a result, a taxonomy of classes of fairness-aware recommender systems is developed along with recommended architectures of awareness-for-fairness.

This paper investigates the issue of fairness for cyber recommendation systems by adopting a multi-sided concept so that multiple individuals are taken into account regarding multiple outcomes to establish user trust in cyberspace. As a result, a taxonomy of classes of fairness-aware recommender systems is developed along with recommended architectures of awareness-for-fairness.