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ORCIDBruno M. Nogueira 0001
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- affiliation: Federal University of Mato Grosso do Sul (UFMS), Campo Grande, Brazil
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2020 – today
- 2023
[j4]Marcos Paulo Silva Gôlo
, Mariana Caravanti de Souza, Rafael Geraldeli Rossi, Solange Oliveira Rezende, Bruno Magalhães Nogueira, Ricardo Marcondes Marcacini:
One-class learning for fake news detection through multimodal variational autoencoders. Eng. Appl. Artif. Intell. 122: 106088 (2023)- [c16]Kenzo Miranda Sakiyama, Lucas de Souza Rodrigues, Bruno Magalhães Nogueira, Edson Takashi Matsubara, Roseli A. F. Romero:
A Framework for Controversial Political Topics Identification Using Twitter Data. BRACIS (3) 2023: 283-298 - 2022
- [j3]Leonardo Fuchs Alves, Francisco J. S. Vasconcellos, Bruno Magalhães Nogueira:
SeSG: a search string generator for Secondary Studies with hybrid search strategies using text mining. Empir. Softw. Eng. 27(5): 105 (2022) - [j2]Mariana Caravanti de Souza, Bruno Magalhães Nogueira, Rafael Geraldeli Rossi, Ricardo Marcondes Marcacini, Brucce Neves dos Santos, Solange Oliveira Rezende:
A network-based positive and unlabeled learning approach for fake news detection. Mach. Learn. 111(10): 3549-3592 (2022) - 2021
- [c15]Mariana Caravanti de Souza, Bruno M. Nogueira, Rafael Geraldeli Rossi, Ricardo M. Marcacini, Solange O. Rezende:
A Heterogeneous Network-Based Positive and Unlabeled Learning Approach to Detect Fake News. BRACIS (2) 2021: 3-18 - [c14]Marcos P. S. Gôlo, Mariana Caravanti de Souza, Rafael Geraldeli Rossi, Solange O. Rezende, Bruno Magalhães Nogueira, Ricardo M. Marcacini:
Learning Textual Representations from Multiple Modalities to Detect Fake News Through One-Class Learning. WebMedia 2021: 197-204 - 2020
- [c13]Vinícios Faustino de Carvalho, Bianca Giacon, Carlos Nascimento, Bruno Magalhães Nogueira:
Machine Learning for Suicidal Ideation Identification on Twitter for the Portuguese Language. BRACIS 2020: 536-550 - [c12]Lucas Akayama Vilhagra, Eraldo Rezende Fernandes, Bruno Magalhães Nogueira:
TextCSN: a semi-supervised approach for text clustering using pairwise constraints and convolutional siamese network. SAC 2020: 1135-1142
2010 – 2019
- 2017
- [c11]Lucas de Souza Rodrigues, Edson Takashi Matsubara, Bruno Magalhães Nogueira:
Learning a Fast Bipartite Ranker for Text Documents Using Lexicographical Rankers and ROC Curves. ICDAR 2017: 1307-1312 - [c10]Ronaldo Florence, Bruno M. Nogueira, Ricardo M. Marcacini:
Constrained Hierarchical Clustering for News Events. IDEAS 2017: 49-56 - [c9]Bruno Magalhães Nogueira, Yuri Karan Benevides Tomas, Ricardo Marcondes Marcacini:
Integrating distance metric learning and cluster-level constraints in semi-supervised clustering. IJCNN 2017: 4118-4125 - 2016
- [c8]Vanessa Araujo Borges, Bruno Magalhães Nogueira, Ellen Francine Barbosa:
A multidimensional data model for the analysis of learning management systems under different perspectives. FIE 2016: 1-8 - 2015
- [j1]Vanessa Araujo Borges, Bruno Magalhães Nogueira, Ellen Francine Barbosa:
Uma análise exploratória de tópicos de pesquisa emergentes em Informática na Educação. Revista Brasileira de Informática na Educ. 23(1): 85-96 (2015) - 2013
- [b1]Bruno Magalhães Nogueira:
Agrupamento hierárquico semissupervisionado ativo baseado em confiança e sua aplicação para extração de hierarquias de tópicos a partir de coleções de documentos. University of São Paulo, Brazil, 2013 - [c7]Robson Motta, Alneu de Andrade Lopes, Bruno M. Nogueira, Solange Oliveira Rezende, Alípio Mário Jorge, Maria Cristina Ferreira de Oliveira:
Comparing relational and non-relational algorithms for clustering propositional data. SAC 2013: 150-155 - 2012
- [c6]Bruno M. Nogueira, Alípio Mário Jorge, Solange Oliveira Rezende:
HCAC: Semi-supervised Hierarchical Clustering Using Confidence-Based Active Learning. Discovery Science 2012: 139-153 - [c5]Bruno M. Nogueira, Alípio Mário Jorge, Solange Oliveira Rezende:
Hierarchical confidence-based active clustering. SAC 2012: 216-219
2000 – 2009
- 2007
- [c4]Bruno M. Nogueira, Tadeu R. A. Santos, Luis E. Zárate:
Comparison of Classifiers Efficiency on Missing Values Recovering: Application in a Marketing Database with Massive Missing Data. CIDM 2007: 66-72 - 2006
- [c3]Luis E. Zárate, Elizabeth Marques Duarte Pereira, Leonardo A. R. Oliveira, Victor P. Gil, Tadeu R. A. Santos, Bruno M. Nogueira:
Techniques for Training Sets Selection in the Representation of a Thermosiphon System Via ANN. IJCNN 2006: 2736-2741 - [c2]Mark A. J. Song, Luis E. Zárate, Sérgio M. Dias, Ana Alvarez, Bruno Soares, Bruno M. Nogueira, Renato Vimieiro, Tadeu R. A. Santos, Newton Vieira:
SOPHIANN: A Tool for Extraction Knowledge Rules from ANN Previously Trained A Case Study. SEKE 2006: 631-638 - [c1]Luis E. Zárate, Bruno Magalhães Nogueira, Tadeu Renato André Santos, Mark Alan Junho Song:
Techniques for Missing Value Recovering in Imbalanced Databases: Application in a Marketing Database with Massive Missing Data. SMC 2006: 2658-2664
Coauthor Index
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