Knowledge discovery from data streams (2010)
- Autores:
- Autor USP: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC
- Unidade: ICMC
- DOI: 10.3233/978-1-60750-611-9-125
- Assuntos: INTELIGÊNCIA ARTIFICIAL; MINERAÇÃO DE DADOS
- Palavras-chave do autor: Data streams; Clustering
- Idioma: Inglês
- Imprenta:
- Fonte:
- Título do periódico: Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web
- Volume/Número/Paginação/Ano: 265 p
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
GAMA, João et al. Knowledge discovery from data streams. Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web. Tradução . Amsterdam: IOS Press, 2010. . Disponível em: https://doi.org/10.3233/978-1-60750-611-9-125. Acesso em: 19 abr. 2024. -
APA
Gama, J., Rodrigues, P. P., Spinosa, E., & Carvalho, A. C. P. de L. F. de. (2010). Knowledge discovery from data streams. In Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web. Amsterdam: IOS Press. doi:10.3233/978-1-60750-611-9-125 -
NLM
Gama J, Rodrigues PP, Spinosa E, Carvalho ACP de LF de. Knowledge discovery from data streams [Internet]. In: Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web. Amsterdam: IOS Press; 2010. [citado 2024 abr. 19 ] Available from: https://doi.org/10.3233/978-1-60750-611-9-125 -
Vancouver
Gama J, Rodrigues PP, Spinosa E, Carvalho ACP de LF de. Knowledge discovery from data streams [Internet]. In: Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web. Amsterdam: IOS Press; 2010. [citado 2024 abr. 19 ] Available from: https://doi.org/10.3233/978-1-60750-611-9-125 - Reduction strategies for hierarchical multi-label classification in protein function prediction
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Informações sobre o DOI: 10.3233/978-1-60750-611-9-125 (Fonte: oaDOI API)
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