A systematic literature review on state-of-the-art deep learning methods for process prediction
Process mining enables the reconstruction and evaluation of business processes based on
digital traces in IT systems. An increasingly important technique in this context is process …
digital traces in IT systems. An increasingly important technique in this context is process …
Deep learning for predictive business process monitoring: Review and benchmark
E Rama-Maneiro, JC Vidal… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
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 …
cases on a business process. Lately, the popularity of deep learning techniques has …
LSTMED: An uneven dynamic process monitoring method based on LSTM and Autoencoder neural network
Due to the complicated production mechanism in multivariate industrial processes, different
dynamic features of variables raise challenges to traditional data-driven process monitoring …
dynamic features of variables raise challenges to traditional data-driven process monitoring …
Explainable predictive business process monitoring using gated graph neural networks
Predictive business process monitoring (PBPM) is a class of techniques designed to forecast
future behaviour of a running process instance or the value of process-related metrics like …
future behaviour of a running process instance or the value of process-related metrics like …
Process outcome prediction: CNN vs. LSTM (with attention)
H Weytjens, J De Weerdt - … Workshops, Seville, Spain, September 13–18 …, 2020 - Springer
The early outcome prediction of ongoing or completed processes confers competitive
advantage to organizations. The performance of classic machine learning and, more …
advantage to organizations. The performance of classic machine learning and, more …
Processtransformer: Predictive business process monitoring with transformer network
Predictive business process monitoring focuses on predicting future characteristics of a
running process using event logs. The foresight into process execution promises great …
running process using event logs. The foresight into process execution promises great …
HAM-Net: Predictive Business Process Monitoring with a hierarchical attention mechanism
One of the essential tasks in Business Process Management (BPM) is Predictive Business
Process Monitoring. This task aims to predict the behavior of an ongoing process based on …
Process Monitoring. This task aims to predict the behavior of an ongoing process based on …
[HTML][HTML] Explainability in process outcome prediction: Guidelines to obtain interpretable and faithful models
A Stevens, J De Smedt - European Journal of Operational Research, 2024 - Elsevier
Process outcome prediction pertains to the classification of ongoing cases of (business)
processes into a given set of categorical outcomes. This field of research has seen a strong …
processes into a given set of categorical outcomes. This field of research has seen a strong …
[HTML][HTML] A technique for determining relevance scores of process activities using graph-based neural networks
Process models generated through process mining depict the as-is state of a process.
Through annotations with metrics such as the frequency or duration of activities, these …
Through annotations with metrics such as the frequency or duration of activities, these …
[PDF][PDF] Remaining time prediction for processes with inter-case dynamics
M Pourbafrani, S Kar, S Kaiser… - … on Process Mining, 2021 - library.oapen.org
Process mining techniques use event data to describe business processes, where the
provided insights are used for predicting processes' future states (Predictive Process …
provided insights are used for predicting processes' future states (Predictive Process …