Efficient computation of multiple density-based clustering hierarchies (2017)
- Authors:
- Autor USP: CAMPELLO, RICARDO JOSÉ GABRIELLI BARRETO - ICMC
- Unidade: ICMC
- DOI: 10.1109/ICDM.2017.127
- Subjects: RECONHECIMENTO DE PADRÕES; MINERAÇÃO DE DADOS; DESCOBERTA DE CONHECIMENTO
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2017
- Source:
- Título: Proceedings
- ISSN: 2374-8486
- Conference titles: IEEE International Conference on Data Mining - ICDM
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
ARAUJO NETO, Antonio Cavalcante et al. Efficient computation of multiple density-based clustering hierarchies. 2017, Anais.. Piscataway: IEEE, 2017. Disponível em: https://doi.org/10.1109/ICDM.2017.127. Acesso em: 25 fev. 2026. -
APA
Araujo Neto, A. C., Sander, J., Campello, R. J. G. B., & Nascimento, M. A. (2017). Efficient computation of multiple density-based clustering hierarchies. In Proceedings. Piscataway: IEEE. doi:10.1109/ICDM.2017.127 -
NLM
Araujo Neto AC, Sander J, Campello RJGB, Nascimento MA. Efficient computation of multiple density-based clustering hierarchies [Internet]. Proceedings. 2017 ;[citado 2026 fev. 25 ] Available from: https://doi.org/10.1109/ICDM.2017.127 -
Vancouver
Araujo Neto AC, Sander J, Campello RJGB, Nascimento MA. Efficient computation of multiple density-based clustering hierarchies [Internet]. Proceedings. 2017 ;[citado 2026 fev. 25 ] Available from: https://doi.org/10.1109/ICDM.2017.127 - Similarity measures for comparing biclusterings
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Informações sobre o DOI: 10.1109/ICDM.2017.127 (Fonte: oaDOI API)
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