RT Journal Article
T1 Deep Learning for Predictive Business Process Monitoring: Review and Benchmark
A1 Rama Maneiro, Efrén
A1 Vidal Aguiar, Juan Carlos
A1 Lama Penín, Manuel
K1 Process mining
K1 Business process monitoring
K1 Neural networks
K1 Systematic literature review
K1 Deep learning
AB Predictive monitoring of business processes is concerned with the prediction of ongoing cases on a business process. Lately, the popularity of deep learning techniques has propitiated an ever-growing set of approaches focused on predictive monitoring based on these techniques. However, the high disparity of event logs and experimental setups used to evaluate these approaches makes it especially difficult to make a fair comparison. Furthermore, it also difficults the selection of the most suitable approach to solve a specific problem. In this article, we provide both a systematic literature review of approaches that use deep learning to tackle the predictive monitoring tasks. In addition, we performed an exhaustive experimental evaluation of 10 different approaches over 12 publicly available event logs.
PB IEEE
SN 1939-1374
YR 2023
FD 2023-02-06
LK https://hdl.handle.net/10347/39151
UL https://hdl.handle.net/10347/39151
LA eng
NO E. Rama-Maneiro, J. C. Vidal and M. Lama, "Deep Learning for Predictive Business Process Monitoring: Review and Benchmark," in IEEE Transactions on Services Computing, vol. 16, no. 1, pp. 739-756, 2023.
NO Consellería de Educación, Universidade e Formación Profesional
NO European Regional Development Fund (ERDF)
NO Ministerio de Ciencia e Innovación
DS Minerva
RD 24 abr 2026