G
Gustavo Paiva Guedes
Researcher at Centro Federal de Educação Tecnológica de Minas Gerais
Publications - 59
Citations - 200
Gustavo Paiva Guedes is an academic researcher from Centro Federal de Educação Tecnológica de Minas Gerais. The author has contributed to research in topics: Sentiment analysis & Brazilian Portuguese. The author has an hindex of 6, co-authored 57 publications receiving 147 citations. Previous affiliations of Gustavo Paiva Guedes include Universidade Tecnológica Federal do Paraná, Medianeira & Centro Federal de Educação Tecnológica Celso Suckow da Fonseca.
Papers
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Journal ArticleDOI
Recent investigations of cascaded GEM and MHSP detectors
Rachel Chechik,Amos Breskin,Gustavo Paiva Guedes,D. Mörmann,J.M. Maia,V. Dangendorf,David Vartsky,J.M.F. dos Santos,J.F.C.A. Veloso +8 more
TL;DR: In this article, the authors present results from their recent investigations on detectors comprising cascaded gas electron multipliers (GEMs) and cascaded GEMs with microhole and strip plate (MHSP) multiplier as a final amplification stage.
Proceedings ArticleDOI
Evaluating the Brazilian Portuguese version of the 2015 LIWC Lexicon with sentiment analysis in social networks
Flavio Carvalho,Rafael Guimarães Rodrigues,Gabriel Santos,Pedro Jacinto Cruz,Lilian Ferrari,Gustavo Paiva Guedes +5 more
TL;DR: In this paper, a new Brazilian Portuguese LIWC lexicon (LIWC 2015pt) based on LIWC 2015 program is presented, which outperforms LIWC 2007pt in all three tasks.
Journal ArticleDOI
Discovering top-k non-redundant clusterings in attributed graphs
TL;DR: RM-CRAG is proposed, a novel algorithm to discover the top-k non-redundant clustering solutions in attributed graphs, i.e., a ranking of clusterings that share the least amount of information, in the information theoretic sense.
Proceedings ArticleDOI
Exploring machine learning methods for the Star/Galaxy Separation Problem
Eduardo Jabbur Machado,Marcello Serqueira,Eduardo Ogasawara,Ricardo L. C. Ogando,M. A. G. Maia,Luiz N. da Costa,Riccardo Campisano,Gustavo Paiva Guedes,Eduardo Bezerra +8 more
TL;DR: A comparative analysis of several machine learning methods targeted at solving the Star/Galaxy Separation Problem at faint magnitudes is presented, of which neural networks and random forest present superior performance.
Journal ArticleDOI
Recent Investigations of Cascaded GEM and MHSP detectors
R. Chechik,Amos Breskin,Gustavo Paiva Guedes,D. Moermann,J.M. Maia,V. Dangendorf,D. Vartzky,J.M.F. dos Santos,J.F.C.A. Veloso +8 more
TL;DR: In this paper, the authors present results from their recent investigations on detectors comprising cascaded gas electron multipliers (GEM) and cascaded GEMs with micro-hole and strip (MHSP) electrodes.