Ponencia
Towards a general architecture for predictive monitoring of business processes
Autor/es | Márquez Chamorro, Alfonso Eduardo
Resinas Arias de Reyna, Manuel Ruiz Cortés, Antonio |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2016 |
Fecha de depósito | 2022-05-24 |
Publicado en |
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Resumen | Process mining allows the extraction of useful information
from event logs and historical data of business processes. This informa tion will improve the performance of these processes and is generally
obtained after they ... Process mining allows the extraction of useful information from event logs and historical data of business processes. This informa tion will improve the performance of these processes and is generally obtained after they have finished. Therefore, predictive monitoring of business process running instances is needed, in order to provide proac tive and corrective actions to improve the process performance and miti gate the possible risks in real time. This monitoring allows the prediction of evaluation metrics for a runtime process. In this context, this work de scribes a general methodology for a business process monitoring system for the prediction of process performance indicators and their stages, such as, the processing and encoding of log events, the calculation of aggregated attributes or the application of a data mining algorithm. |
Agencias financiadoras | Ministerio de Economía y Competitividad (MINECO). España Junta de Andalucía |
Identificador del proyecto | BELI (TIN2015-70560-R)
COPAS (P12–TIC-1867)) |
Cita | Márquez Chamorro, A.E., Resinas Arias de Reyna, M. y Ruiz Cortés, A. (2016). Towards a general architecture for predictive monitoring of business processes. En JCIS 2016: XII Jornadas de Ingeniería de Ciencia e Ingeniería de Servicios Salamanca, España: Asociación de Ingeniería del Software y Tecnologías de Desarrollo de Software (SISTEDES). |
Ficheros | Tamaño | Formato | Ver | Descripción |
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JCIS2016_paper_19.pdf | 156.5Kb | [PDF] | Ver/ | |