Process mining through artificial neural networks and support vector machines: a systematic literature review (2015)
- Authors:
- USP affiliated authors: PERES, SARAJANE MARQUES - EACH ; FANTINATO, MARCELO - EACH
- Unidade: EACH
- DOI: 10.1108/BPMJ-02-2015-0017
- Assunto: PRODUÇÃO CIENTÍFICA
- Language: Inglês
- Imprenta:
- Source:
- Título: Business Process Management Journal
- ISSN: 1463-7154
- Volume/Número/Paginação/Ano: v. 21, n. 6, p. 1391-1415, 2015
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
MAITA, Ana Rocío Cárdenas et al. Process mining through artificial neural networks and support vector machines: a systematic literature review. Business Process Management Journal, v. 21, n. 6, p. 1391-1415, 2015Tradução . . Disponível em: https://doi.org/10.1108/BPMJ-02-2015-0017. Acesso em: 28 dez. 2025. -
APA
Maita, A. R. C., Martins, L. C., Paz , C. R. L., Peres, S. M., & Fantinato, M. (2015). Process mining through artificial neural networks and support vector machines: a systematic literature review. Business Process Management Journal, 21( 6), 1391-1415. doi:10.1108/BPMJ-02-2015-0017 -
NLM
Maita ARC, Martins LC, Paz CRL, Peres SM, Fantinato M. Process mining through artificial neural networks and support vector machines: a systematic literature review [Internet]. Business Process Management Journal. 2015 ; 21( 6): 1391-1415.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1108/BPMJ-02-2015-0017 -
Vancouver
Maita ARC, Martins LC, Paz CRL, Peres SM, Fantinato M. Process mining through artificial neural networks and support vector machines: a systematic literature review [Internet]. Business Process Management Journal. 2015 ; 21( 6): 1391-1415.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1108/BPMJ-02-2015-0017 - Enhancing completion time prediction through attribute selection
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Informações sobre o DOI: 10.1108/BPMJ-02-2015-0017 (Fonte: oaDOI API)
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