Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection (2020)
- Authors:
- Autor USP: MELLO, RODRIGO FERNANDES DE - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-030-61380-8_44
- Subjects: MINERAÇÃO DE DADOS; ANÁLISE DE SÉRIES TEMPORAIS; MÍDIAS SOCIAIS
- Keywords: Temporal graph; Concept Drift; Social networks
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Lecture Notes in Artificial Intelligence
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 12320, p. 650-664, 2020
- Conference titles: Brazilian Conference on Intelligent Systems - BRACIS
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
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: 12 fev. 2026. , 2020 -
APA
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_44 -
NLM
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 2026 fev. 12 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_44 -
Vancouver
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 2026 fev. 12 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_44 - A novel approach to quantify novelty levels applied on ubiquitous music distribution
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Informações sobre o DOI: 10.1007/978-3-030-61380-8_44 (Fonte: oaDOI API)
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