Active learning strategies for semi-supervised DBSCAN (2014)
- Authors:
- Autor USP: CAMPELLO, RICARDO JOSÉ GABRIELLI BARRETO - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-319-06483-3_16
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Source:
- Título: Lecture Notes in Artificial Intelligence
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 8436, p. 179-190, 2014
- Conference titles: Canadian Conference on Artificial Intelligence : Advances in Artificial Intelligence - Canadian AI
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
LI, Jundong et al. Active learning strategies for semi-supervised DBSCAN. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-06483-3_16. Acesso em: 10 jan. 2026. , 2014 -
APA
Li, J., Sander, J., Campello, R. J. G. B., & Zimek, A. (2014). Active learning strategies for semi-supervised DBSCAN. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-319-06483-3_16 -
NLM
Li J, Sander J, Campello RJGB, Zimek A. Active learning strategies for semi-supervised DBSCAN [Internet]. Lecture Notes in Artificial Intelligence. 2014 ; 8436 179-190.[citado 2026 jan. 10 ] Available from: https://doi.org/10.1007/978-3-319-06483-3_16 -
Vancouver
Li J, Sander J, Campello RJGB, Zimek A. Active learning strategies for semi-supervised DBSCAN [Internet]. Lecture Notes in Artificial Intelligence. 2014 ; 8436 179-190.[citado 2026 jan. 10 ] Available from: https://doi.org/10.1007/978-3-319-06483-3_16 - A cluster based hybrid feature selection approach
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Informações sobre o DOI: 10.1007/978-3-319-06483-3_16 (Fonte: oaDOI API)
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