Privileged information for hierarchical document clustering: a metric learning approach (2014)
- Authors:
- USP affiliated authors: HRUSCHKA, EDUARDO RAUL - ICMC ; REZENDE, SOLANGE OLIVEIRA - ICMC
- Unidade: ICMC
- DOI: 10.1109/ICPR.2014.625
- Subjects: INTELIGÊNCIA ARTIFICIAL; MINERAÇÃO DE DADOS; APRENDIZADO COMPUTACIONAL
- Language: Inglês
- Imprenta:
- Publisher: Conference Publishing Services
- Publisher place: Los Alamitos
- Date published: 2014
- Source:
- Título do periódico: Proceedings
- ISSN: 1051-4651
- Conference titles: International Conference on Pattern Recognition - ICPR
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
MARCACINI, Ricardo M et al. Privileged information for hierarchical document clustering: a metric learning approach. 2014, Anais.. Los Alamitos: Conference Publishing Services, 2014. Disponível em: https://doi.org/10.1109/ICPR.2014.625. Acesso em: 24 abr. 2024. -
APA
Marcacini, R. M., Domingues, M. A., Hruschka, E. R., & Rezende, S. O. (2014). Privileged information for hierarchical document clustering: a metric learning approach. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/ICPR.2014.625 -
NLM
Marcacini RM, Domingues MA, Hruschka ER, Rezende SO. Privileged information for hierarchical document clustering: a metric learning approach [Internet]. Proceedings. 2014 ;[citado 2024 abr. 24 ] Available from: https://doi.org/10.1109/ICPR.2014.625 -
Vancouver
Marcacini RM, Domingues MA, Hruschka ER, Rezende SO. Privileged information for hierarchical document clustering: a metric learning approach [Internet]. Proceedings. 2014 ;[citado 2024 abr. 24 ] Available from: https://doi.org/10.1109/ICPR.2014.625 - On the use of consensus clustering for incremental learning of topic hierarchies
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- Transfer learning with cluster ensembles
- An Experimental Study on Unsupervised Clustering-Based Feature Selection Methods
- On the influence of imputation in classification: practical issues
- Towards improving cluster-based feature selection with a simplified silhouette filter
- Document clustering for forensic computing: an approach for improving computer inspection
- Document clustering for forensic analysis: an approach for improving computer inspection
Informações sobre o DOI: 10.1109/ICPR.2014.625 (Fonte: oaDOI API)
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