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Filtros : "ACM Transactions on Knowledge Discovery from Data" "Inglês" Removido: "MINERAÇÃO DE DADOS" Limpar

Filtros

USP affiliated authors
- hruschka, eduardo raul (~1)
- minghim, rosane (~1)
- oliveira, maria cristina ferreira de (~1)
Date published
- 2018 (~1)
- 2014 (~1)
Subjects
- algoritmos (1)
- computação gráfica (1)
- inteligência artificial (1)
- mídias sociais (1)
- reconhecimento de padrões (1)

Artigo de periodico
ATR-Vis: visual and interactive information retrieval for parliamentary discussions in Twitter (2018)
Makki, Raheleh; Carvalho, Eder; Soto, Axel J; Brooks, Stephen; Oliveira, Maria Cristina Ferreira de ; Milios, Evangelos; Minghim, Rosane
Source: ACM Transactions on Knowledge Discovery from Data. Unidade: ICMC
Subjects: COMPUTAÇÃO GRÁFICA, RECUPERAÇÃO DA INFORMAÇÃO, MÍDIAS SOCIAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MAKKI, Raheleh et al. ATR-Vis: visual and interactive information retrieval for parliamentary discussions in Twitter. ACM Transactions on Knowledge Discovery from Data, v. 12, n. 1, p. 3:1-3:33, 2018Tradução . . Disponível em: https://doi.org/10.1145/3047010. Acesso em: 28 nov. 2025.
APA
Makki, R., Carvalho, E., Soto, A. J., Brooks, S., Oliveira, M. C. F. de, Milios, E., & Minghim, R. (2018). ATR-Vis: visual and interactive information retrieval for parliamentary discussions in Twitter. ACM Transactions on Knowledge Discovery from Data, 12( 1), 3:1-3:33. doi:10.1145/3047010
NLM
Makki R, Carvalho E, Soto AJ, Brooks S, Oliveira MCF de, Milios E, Minghim R. ATR-Vis: visual and interactive information retrieval for parliamentary discussions in Twitter [Internet]. ACM Transactions on Knowledge Discovery from Data. 2018 ; 12( 1): 3:1-3:33.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1145/3047010
Vancouver
Makki R, Carvalho E, Soto AJ, Brooks S, Oliveira MCF de, Milios E, Minghim R. ATR-Vis: visual and interactive information retrieval for parliamentary discussions in Twitter [Internet]. ACM Transactions on Knowledge Discovery from Data. 2018 ; 12( 1): 3:1-3:33.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1145/3047010
Artigo de periodico
An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning (2014)
Acharya, Ayan; Hruschka, Eduardo Raul ; Ghosh, Joydeep; Acharyya, Sreangsu
Source: ACM Transactions on Knowledge Discovery from Data. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, RECONHECIMENTO DE PADRÕES, ALGORITMOS, VISÃO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ACHARYA, Ayan et al. An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning. ACM Transactions on Knowledge Discovery from Data, v. 9, n. 1, p. 1:1-1:35, 2014Tradução . . Disponível em: https://doi.org/10.1145/2601435. Acesso em: 28 nov. 2025.
APA
Acharya, A., Hruschka, E. R., Ghosh, J., & Acharyya, S. (2014). An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning. ACM Transactions on Knowledge Discovery from Data, 9( 1), 1:1-1:35. doi:10.1145/2601435
NLM
Acharya A, Hruschka ER, Ghosh J, Acharyya S. An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning [Internet]. ACM Transactions on Knowledge Discovery from Data. 2014 ; 9( 1): 1:1-1:35.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1145/2601435
Vancouver
Acharya A, Hruschka ER, Ghosh J, Acharyya S. An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning [Internet]. ACM Transactions on Knowledge Discovery from Data. 2014 ; 9( 1): 1:1-1:35.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1145/2601435

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