‪Julio Barbieri‬ - ‪Google Scholar‬

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	All	Since 2019
Citations	33	28
h-index	2	2
i10-index	1	1

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Co-authors

Filipe Braida do CarmoUniversidade Federal Rural do Rio de Janeiro (UFRRJ)Verified email at ufrrj.br
Geraldo ZimbraoProfessor de Ciência da ComputaçãoVerified email at cos.ufrj.br
Leandro AlvimUFRRJ, professor de ciência da ComputaçãoVerified email at ufrrj.br

Julio Barbieri

Julio Barbieri

D.Sc., Systems and Computer Engineering, COPPE/UFRJ

Verified email at cos.ufrj.br

Machine Learning Recommender Systems Deep Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Autoencoders and recommender systems: COFILS approach J Barbieri, LGM Alvim, F Braida, G Zimbrão Expert Systems with Applications 89, 81-90, 2017	30	2017
Simulating real profiles for shilling attacks: A generative approach J Barbieri, LGM Alvim, F Braida, G Zimbrao Knowledge-Based Systems 230, 107390, 2021	3	2021
When autoencoders meet recommender systems: COFILS approach JCBG Almeida Universidade Federal do Rio de Janeiro, 2017		2017
Particionamento Vertical de Dados em Filtragem Colaborativa RS Ferreira, JCBG Almeida, KP Cotta, F Braida, G Zimbrao

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Articles 1–4