Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs (2017)
- Authors:
- Autor USP: LOPES, ALNEU DE ANDRADE - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.patrec.2016.04.006
- Subjects: INTELIGÊNCIA ARTIFICIAL; APRENDIZADO COMPUTACIONAL; MINERAÇÃO DE DADOS
- Keywords: Text classification; Transductive learning; Graph-based learning; Label propagation; Bipartite graphs
- Language: Inglês
- Imprenta:
- Source:
- Título: Pattern Recognition Letters
- ISSN: 0167-8655
- Volume/Número/Paginação/Ano: v. 87, p. 127-138, Feb. 2017
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
FALEIROS, Thiago de Paulo e ROSSI, Rafael Geraldeli e LOPES, Alneu de Andrade. Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs. Pattern Recognition Letters, v. 87, p. 127-138, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.patrec.2016.04.006. Acesso em: 16 fev. 2026. -
APA
Faleiros, T. de P., Rossi, R. G., & Lopes, A. de A. (2017). Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs. Pattern Recognition Letters, 87, 127-138. doi:10.1016/j.patrec.2016.04.006 -
NLM
Faleiros T de P, Rossi RG, Lopes A de A. Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs [Internet]. Pattern Recognition Letters. 2017 ; 87 127-138.[citado 2026 fev. 16 ] Available from: https://doi.org/10.1016/j.patrec.2016.04.006 -
Vancouver
Faleiros T de P, Rossi RG, Lopes A de A. Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs [Internet]. Pattern Recognition Letters. 2017 ; 87 127-138.[citado 2026 fev. 16 ] Available from: https://doi.org/10.1016/j.patrec.2016.04.006 - A multi-view approach for semi-supervised scientific paper classification
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Informações sobre o DOI: 10.1016/j.patrec.2016.04.006 (Fonte: oaDOI API)
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