In fact, our experimental results on real data show that improvement in fairness and diversity tends to increase the user acceptance rate of the recommendations.

Apr 23, 2017 · In this paper, we addressed an important issue of fairness to the creators while providing relevant and diverse recommendations to the consumers ...

Dec 23, 2021 · We propose a re-ranking strategy that can be applied to the scored recommendation lists to improve exposure distribution across the creators ( ...

Fairness Aware Recommendations on Behance. PAKDD. Publication date: May 23, 2017. Natwar Modani, Deepali Jain, Ujjawal Soni, Gaurav Kumar Gupta, Palak Agarwal.

We show that our method results in recommendations that have much higher level of fairness and representative diversity compared to the state-of-art ...

We review over 60 papers published in top conferences/journals, including TOIS, SIGIR, and WWW. First, we summarize fairness definitions in the recommendation.

Challenging social media threats using collective well-being-aware recommendation algorithms and an educational virtual companion · Education, Computer Science.

We introduce some widely used measurements for fairness in recommendation and review fairness-related recommendation datasets in previous studies. • We review ...

A table of publications on fairness in recommender systems. This page will be periodically updated to include the most recent works.

In this work, we propose a fairness-aware multi-stakeholder recommender system that uses a multi-objective evolutionary algorithm to make a trade-off between ...