Fonte: PLOS One. Unidades: IFSC, ICMC
Assuntos: CIÊNCIA DA COMPUTAÇÃO, REDES NEURAIS, APRENDIZADO COMPUTACIONAL
ABNT
SILVA, Giovana Daniele da et al. Using full-text content to characterize and identify best seller books: a study of early 20th-century literature. PLOS One, v. 19, n. 4, p. e0302070-1-e0302070-20 + supporting information, 2024Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0302070. Acesso em: 09 nov. 2024.APA
Silva, G. D. da, Silva, F. N., Arruda, H. F. de, Souza, B. C. e, Costa, L. da F., & Amancio, D. R. (2024). Using full-text content to characterize and identify best seller books: a study of early 20th-century literature. PLOS One, 19( 4), e0302070-1-e0302070-20 + supporting information. doi:10.1371/journal.pone.0302070NLM
Silva GD da, Silva FN, Arruda HF de, Souza BC e, Costa L da F, Amancio DR. Using full-text content to characterize and identify best seller books: a study of early 20th-century literature [Internet]. PLOS One. 2024 ; 19( 4): e0302070-1-e0302070-20 + supporting information.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1371/journal.pone.0302070Vancouver
Silva GD da, Silva FN, Arruda HF de, Souza BC e, Costa L da F, Amancio DR. Using full-text content to characterize and identify best seller books: a study of early 20th-century literature [Internet]. PLOS One. 2024 ; 19( 4): e0302070-1-e0302070-20 + supporting information.[citado 2024 nov. 09 ] Available from: https://doi.org/10.1371/journal.pone.0302070