Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Similares en SciELO
Compartir
RISTI - Revista Ibérica de Sistemas e Tecnologias de Informação
versión impresa ISSN 1646-9895
Resumen
RIVAS, Marcos Hernán y BAYONA-ORE, Sussy. Process Mining Algorithms for Automated Process Discovery. RISTI [online]. 2019, n.31, pp.33-49. ISSN 1646-9895. https://doi.org/10.17013/risti.31.33-49.
A fundamental aspect to manage and execute business processes is theprocess modeling. In order to establish the differences that exist between the pre- established models and the models that have been executed, the traces and records of events must be reviewed. Process Mining uses event logs to discover the real processes, through the extraction of knowledge. To know which algorithms have been developed for the automatic discovery of business processes, a literature review of articles published in the period 2004-2017 was carried out. As a result of the review, 20 primary articles were identified and analyzed. A total of 20 algorithms were identified using different approaches with predominance of the general algorithm approach. The algorithms identified mostly use Petri networks as a process modeling technique
Palabras clave : Petri networks; automatic discovery; process mining; process model; event log.