Resumen
A fundamental aspect to manage and execute business processes is the process 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.
Título traducido de la contribución | Process mining algorithms for automated process discovery |
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Idioma original | Español |
Páginas (desde-hasta) | 33-49 |
Número de páginas | 17 |
Publicación | RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao |
Volumen | 2019 |
N.º | 31 |
DOI | |
Estado | Publicada - 2019 |
Publicado de forma externa | Sí |
Palabras clave
- Automatic discovery
- Event log
- Petri networks
- Process mining
- Process model