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20172022
most citedEquality of Learning Opportunity via Individual Fairness in Personalized Recommendations

53 citations · 64 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.IR2022★ 7 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.IR2022

Robust Reputation Independence in Ranking Systems for Multiple Sensitive Attributes

Guilherme Ramos, Ludovico Boratto, Mirko Marras

Ranking systems have an unprecedented influence on how and what information people access, and their impact on our society is being analyzed from different perspectives, such as us…

cs.IR2020★ 53 cited

Equality of Learning Opportunity via Individual Fairness in Personalized Recommendations

Mirko Marras, Ludovico Boratto, Guilherme Ramos +1

Online educational platforms are playing a primary role in mediating the success of individuals' careers. Therefore, while building overlying content recommendation services, it be…

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…

cs.IR2017★ 2 cited

Recommendation via matrix completion using Kolmogorov complexity

Guilherme Ramos, Joao Saude, Carlos Caleiro +1

A usual way to model a recommendation system is as a matrix completion problem. There are several matrix completion methods, typically using optimization approaches or collaborativ…

cs.IR2017★ 2 cited

Robust reputation-based ranking on multipartite rating networks

João Saúde, Guilherme Ramos, Carlos Caleiro +1

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