most citedConnecting User and Item Perspectives in Popularity Debiasing for Collaborative Recommendation

136 citations · 189 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022

The More Secure, The Less Equally Usable: Gender and Ethnicity (Un)fairness of Deep Face Recognition along Security Thresholds

Andrea Atzori, Gianni Fenu, Mirko Marras

Face biometrics are playing a key role in making modern smart city applications more secure and usable. Commonly, the recognition threshold of a face recognition system is adjusted…

cs.IR20227 cited

Regulating Group Exposure for Item Providers in Recommendation

Mirko Marras, Ludovico Boratto, Guilherme Ramos +1

Engaging all content providers, including newcomers or minority demographic groups, is crucial for online platforms to keep growing and working. Hence, while building recommendatio…

cs.IR202246 cited

Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations

Giacomo Balloccu, Ludovico Boratto, Gianni Fenu +1

Existing explainable recommender systems have mainly modeled relationships between recommended and already experienced products, and shaped explanation types accordingly (e.g., mov…

cs.IR2020136 cited

Connecting User and Item Perspectives in Popularity Debiasing for Collaborative Recommendation

Ludovico Boratto, Gianni Fenu, Mirko Marras

Recommender systems learn from historical users' feedback that is often non-uniformly distributed across items. As a consequence, these systems may end up suggesting popular items…

cs.IR2020

ECIR 2020 Workshops: Assessing the Impact of Going Online

Sérgio Nunes, Suzanne Little, Sumit Bhatia +11

ECIR 2020 https://ecir2020.org/ was one of the many conferences affected by the COVID-19 pandemic. The Conference Chairs decided to keep the initially planned dates (April 14-17, 2…