Artículo
Run-time prediction of business process indicators using evolutionary decision rules
Autor/es | Márquez Chamorro, Alfonso Eduardo
Resinas Arias de Reyna, Manuel Ruiz Cortés, Antonio Toro Bonilla, Miguel |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2017 |
Fecha de depósito | 2020-09-24 |
Publicado en |
|
Resumen | Predictive monitoring of business processes is a challenging topic of process mining which is concerned with the prediction of process indicators of running process instances. The main value of predictive monitoring is to ... Predictive monitoring of business processes is a challenging topic of process mining which is concerned with the prediction of process indicators of running process instances. The main value of predictive monitoring is to provide information in order to take proactive and corrective actions to improve process performance and mitigate risks in real time. In this paper, we present an approach for predictive monitoring based on the use of evolutionary algorithms. Our method provides a novel event window-based encoding and generates a set of decision rules for the run-time prediction of process indicators according to event log properties. These rules can be interpreted by users to extract further insight of the business processes while keeping a high level of accuracy. Furthermore, a full software stack consisting of a tool to support the training phase and a framework that enables the integration of run-time predictions with business process management systems, has been developed. Obtained results show the validity of our proposal for two large real-life datasets: BPI Challenge 2013 and IT Department of Andalusian Health Service (SAS). |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España Junta de Andalucía |
Identificador del proyecto | TIN2015-70560-R
P12TIC-1867 |
Cita | Márquez Chamorro, A.E., Resinas Arias de Reyna, M., Ruiz Cortés, A. y Toro Bonilla, M. (2017). Run-time prediction of business process indicators using evolutionary decision rules. Expert Systems with Applications, 87 (november 2017), 1-14. |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
Run-time prediction of business.pdf | 2.262Mb | [PDF] | Ver/ | |