activity
20202022
most citedConnecting User and Item Perspectives in Popularity Debiasing for Collaborative Recommendation

136 citations · 189 across the 6 of their papers we have counts for

collaborators

6 papers

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.CY2021

What's Your Value of Travel Time? Collecting Traveler-Centered Mobility Data via Crowdsourcing

Cristian Consonni, Silvia Basile, Matteo Manca +5

Mobility and transport, by their nature, involve crowds and require the coordination of multiple stakeholders - such as policy-makers, planners, transport operators, and the travel…

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…

cs.IR2020

A Robust Reputation-based Group Ranking System and its Resistance to Bribery

Joao Saude, Guilherme Ramos, Ludovico Boratto +1

The spread of online reviews and opinions and its growing influence on people's behavior and decisions, boosted the interest to extract meaningful information from this data deluge…