Santos, Victor M. G. dos; Mello, Rodrigo Fernandes de 
; Nogueira, Tatiane ; Rios, Ricardo A
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS, MÍDIAS SOCIAIS
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ABNT
SANTOS, Victor M. G. dos et al. Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_44. Acesso em: 05 nov. 2025. , 2020APA
Santos, V. M. G. dos, Mello, R. F. de, Nogueira, T., & Rios, R. A. (2020). Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_44NLM
Santos VMG dos, Mello RF de, Nogueira T, Rios RA. Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 650-664.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_44Vancouver
Santos VMG dos, Mello RF de, Nogueira T, Rios RA. Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 650-664.[citado 2025 nov. 05 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_44
