Unsupervised active learning techniques for labeling training sets: an experimental evaluation on sequential data (2017)
- Authors:
- USP affiliated authors: BATISTA, GUSTAVO ENRIQUE DE ALMEIDA PRADO ALVES - ICMC ; REZENDE, SOLANGE OLIVEIRA - ICMC
- Unidade: ICMC
- DOI: 10.3233/IDA-163075
- Subjects: APRENDIZADO COMPUTACIONAL; RECONHECIMENTO DE PADRÕES; ANÁLISE DE SÉRIES TEMPORAIS
- Keywords: Unsupervised active learning; training set labeling; clustering; centrality measures; sequential data
- Language: Inglês
- Imprenta:
- Source:
- Título: Intelligent Data Analysis
- ISSN: 1088-467X
- Volume/Número/Paginação/Ano: v. 21, n. 5, p. 1061-1095, 2017
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SOUZA, Vinícius M. A et al. Unsupervised active learning techniques for labeling training sets: an experimental evaluation on sequential data. Intelligent Data Analysis, v. 21, n. 5, p. 1061-1095, 2017Tradução . . Disponível em: https://doi.org/10.3233/IDA-163075. Acesso em: 28 fev. 2026. -
APA
Souza, V. M. A., Rossi, R. G., Batista, G. E. de A. P. A., & Rezende, S. O. (2017). Unsupervised active learning techniques for labeling training sets: an experimental evaluation on sequential data. Intelligent Data Analysis, 21( 5), 1061-1095. doi:10.3233/IDA-163075 -
NLM
Souza VMA, Rossi RG, Batista GE de APA, Rezende SO. Unsupervised active learning techniques for labeling training sets: an experimental evaluation on sequential data [Internet]. Intelligent Data Analysis. 2017 ; 21( 5): 1061-1095.[citado 2026 fev. 28 ] Available from: https://doi.org/10.3233/IDA-163075 -
Vancouver
Souza VMA, Rossi RG, Batista GE de APA, Rezende SO. Unsupervised active learning techniques for labeling training sets: an experimental evaluation on sequential data [Internet]. Intelligent Data Analysis. 2017 ; 21( 5): 1061-1095.[citado 2026 fev. 28 ] Available from: https://doi.org/10.3233/IDA-163075 - Improving the recommendation of given names by using contextual information
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Informações sobre o DOI: 10.3233/IDA-163075 (Fonte: oaDOI API)
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