Computer Science researchBelo Horizonte, Brasil · Since 2017

Research Topic

Recommender systems

Methods for finding relevant items, exploring preferences and investigating bias in recommender systems.

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What we investigate

A research topic present in the group’s recommendation studies and, in 2024, in the EQNet paper on popularity bias in collaborative filtering.

Collaborative research

To learn about the researchers involved, the latest results and ways to participate in this project, contact the coordination team.

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Reading on this topic

Work related to this topic.

2024

Conference paper · Natural language

EQNet: A Post-Processing Approach to Manage Popularity Bias in Collaborative Filter Recommender Systems

Gabriel Bálbio Vieira Machado, Wladmir Cardoso Brandão, Humberto Torres Marques Neto

26th International Conference on Enterprise Information Systems · 2024

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2021

Conference paper · Information retrieval

RECAID: A Sponsorship Recommendation Approach

William Johnny Bernardes de Oliveira, Wladmir Cardoso Brandão

23rd International Conference on Enterprise Information Systems · 2021

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2018

Conference paper · Information retrieval

Recommending Scientific Collaboration from ResearchGate

Marcos Wander Rodrigues, Wladmir Cardoso Brandão, Luis Enrique Zárate Gálvez

2018 7th Brazilian Conference on Intelligent Systems (BRACIS) · 2018

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