26 citations · 76 across the 11 of their papers we have counts for
6 papers · 1 filter
Distributionally-Informed Recommender System Evaluation
Michael D. Ekstrand, Ben Carterette, Fernando Diaz
Current practice for evaluating recommender systems typically focuses on point estimates of user-oriented effectiveness metrics or business metrics, sometimes combined with additio…
The Impact of Group Membership Bias on the Quality and Fairness of Exposure in Ranking
Ali Vardasbi, Maarten de Rijke, Fernando Diaz +1
When learning to rank from user interactions, search and recommender systems must address biases in user behavior to provide a high-quality ranking. One type of bias that has recen…
Commonality in Recommender Systems: Evaluating Recommender Systems to Enhance Cultural Citizenship
Andres Ferraro, Gustavo Ferreira, Fernando Diaz +1
Recommender systems have become the dominant means of curating cultural content, significantly influencing individual cultural experience. Since recommender systems tend to optimiz…
On Natural Language User Profiles for Transparent and Scrutable Recommendation
Filip Radlinski, Krisztian Balog, Fernando Diaz +2
Natural interaction with recommendation and personalized search systems has received tremendous attention in recent years. We focus on the challenge of supporting people's understa…
Joint Multisided Exposure Fairness for Recommendation
Haolun Wu, Bhaskar Mitra, Chen Ma +2
Prior research on exposure fairness in the context of recommender systems has focused mostly on disparities in the exposure of individual or groups of items to individual users of…
Multi-FR: A Multi-objective Optimization Framework for Multi-stakeholder Fairness-aware Recommendation
Haolun Wu, Chen Ma, Bhaskar Mitra +2
Nowadays, most online services are hosted on multi-stakeholder marketplaces, where consumers and producers may have different objectives. Conventional recommendation systems, howev…