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Trabalho de evento-anais periodico
Food truck recommendation using multi-label classification (2017)
Rivolli, Adriano; Parker, Larissa C; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: EPIA Conference on Artificial Intelligence - EPIA. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RIVOLLI, Adriano e PARKER, Larissa C e CARVALHO, André Carlos Ponce de Leon Ferreira de. Food truck recommendation using multi-label classification. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-65340-2_48. Acesso em: 04 nov. 2025. , 2017
APA
Rivolli, A., Parker, L. C., & Carvalho, A. C. P. de L. F. de. (2017). Food truck recommendation using multi-label classification. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-319-65340-2_48
NLM
Rivolli A, Parker LC, Carvalho ACP de LF de. Food truck recommendation using multi-label classification [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10423 585-596.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1007/978-3-319-65340-2_48
Vancouver
Rivolli A, Parker LC, Carvalho ACP de LF de. Food truck recommendation using multi-label classification [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10423 585-596.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1007/978-3-319-65340-2_48
Trabalho de evento-anais periodico
A lightweight regression method to infer psycholinguistic properties for brazilian portuguese (2017)
Santos, Leandro Borges dos; Duran, Magali Sanches; Hartmann, Nathan Siegle; Candido Junior, Arnaldo; Paetzold, Gustavo Henrique; Aluísio, Sandra Maria
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: International Conference on Text, Speech, and Dialogue - TSD. Unidade: ICMC
Assuntos: PROCESSAMENTO DE LINGUAGEM NATURAL, PSICOLINGUÍSTICA, PORTUGUÊS DO BRASIL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Leandro Borges dos et al. A lightweight regression method to infer psycholinguistic properties for brazilian portuguese. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-64206-2_32. Acesso em: 04 nov. 2025. , 2017
APA
Santos, L. B. dos, Duran, M. S., Hartmann, N. S., Candido Junior, A., Paetzold, G. H., & Aluísio, S. M. (2017). A lightweight regression method to infer psycholinguistic properties for brazilian portuguese. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-319-64206-2_32
NLM
Santos LB dos, Duran MS, Hartmann NS, Candido Junior A, Paetzold GH, Aluísio SM. A lightweight regression method to infer psycholinguistic properties for brazilian portuguese [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10415 281-289.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1007/978-3-319-64206-2_32
Vancouver
Santos LB dos, Duran MS, Hartmann NS, Candido Junior A, Paetzold GH, Aluísio SM. A lightweight regression method to infer psycholinguistic properties for brazilian portuguese [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10415 281-289.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1007/978-3-319-64206-2_32
Trabalho de evento-resumo
Recommending collaborative filtering algorithms using subsampling landmarkers (2017)
Cunha, Tiago; Soares, Carlos; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: International Conference on Discovery Science - DS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CUNHA, Tiago e SOARES, Carlos e CARVALHO, André Carlos Ponce de Leon Ferreira de. Recommending collaborative filtering algorithms using subsampling landmarkers. 2017, Anais.. Cham: Springer, 2017. p. 189-203. Disponível em: https://doi.org/10.1007/978-3-319-67786-6_14. Acesso em: 04 nov. 2025.
APA
Cunha, T., Soares, C., & Carvalho, A. C. P. de L. F. de. (2017). Recommending collaborative filtering algorithms using subsampling landmarkers. In Lecture Notes in Artificial Intelligence (Vol. 10558, p. 189-203). Cham: Springer. doi:10.1007/978-3-319-67786-6_14
NLM
Cunha T, Soares C, Carvalho ACP de LF de. Recommending collaborative filtering algorithms using subsampling landmarkers [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10558 189-203.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1007/978-3-319-67786-6_14
Vancouver
Cunha T, Soares C, Carvalho ACP de LF de. Recommending collaborative filtering algorithms using subsampling landmarkers [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10558 189-203.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1007/978-3-319-67786-6_14
Trabalho de evento-anais periodico
Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques (2017)
Oliva, Jefferson Tales; Rosa, João Luís Garcia
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Banff International Research Station for Mathematical Innovation and Discovery Workshop - BIRS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, RECONHECIMENTO DE PADRÕES, ELETROENCEFALOGRAFIA, EPILEPSIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVA, Jefferson Tales e ROSA, João Luís Garcia. Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-69775-8_7. Acesso em: 04 nov. 2025. , 2017
APA
Oliva, J. T., & Rosa, J. L. G. (2017). Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-319-69775-8_7
NLM
Oliva JT, Rosa JLG. Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10344 134-145.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1007/978-3-319-69775-8_7
Vancouver
Oliva JT, Rosa JLG. Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10344 134-145.[citado 2025 nov. 04 ] Available from: https://doi.org/10.1007/978-3-319-69775-8_7

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