A systematic literature review on state-of-the-art deep learning methods for process prediction

DA Neu, J Lahann, P Fettke - Artificial Intelligence Review, 2022 - Springer
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 …

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 …

Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring

I Verenich, M Dumas, ML Rosa, FM Maggi… - ACM Transactions on …, 2019 - dl.acm.org
Predictive business process monitoring methods exploit historical process execution logs to
generate predictions about running instances (called cases) of a business process, such as …

Explainable predictive process monitoring

R Galanti, B Coma-Puig, M de Leoni… - … on Process Mining …, 2020 - ieeexplore.ieee.org
Predictive Business Process Monitoring is becoming an essential aid for organizations,
providing online operational support of their processes. This paper tackles the fundamental …

Explainable predictive business process monitoring using gated graph neural networks

M Harl, S Weinzierl, M Stierle… - Journal of Decision …, 2020 - Taylor & Francis
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 …

[HTML][HTML] Process data properties matter: Introducing gated convolutional neural networks (GCNN) and key-value-predict attention networks (KVP) for next event …

K Heinrich, P Zschech, C Janiesch, M Bonin - Decision Support Systems, 2021 - Elsevier
Predicting next events in predictive process monitoring enables companies to manage and
control processes at an early stage and reduce their action distance. In recent years …

Object-centric process predictive analytics

R Galanti, M De Leoni, N Navarin, A Marazzi - Expert Systems with …, 2023 - Elsevier
Object-centric processes (also known as Artifact-centric processes) are implementations of a
paradigm where an instance of one process is not executed in isolation but interacts with …

Processtransformer: Predictive business process monitoring with transformer network

ZA Bukhsh, A Saeed, RM Dijkman - arXiv preprint arXiv:2104.00721, 2021 - arxiv.org
Predictive business process monitoring focuses on predicting future characteristics of a
running process using event logs. The foresight into process execution promises great …

Learning uncertainty with artificial neural networks for predictive process monitoring

H Weytjens, J De Weerdt - Applied Soft Computing, 2022 - Elsevier
The inability of artificial neural networks to assess the uncertainty of their predictions is an
impediment to their widespread use. We distinguish two types of learnable uncertainty …

Darwin: An online deep learning approach to handle concept drifts in predictive process monitoring

V Pasquadibisceglie, A Appice, G Castellano… - … Applications of Artificial …, 2023 - Elsevier
Predictive process monitoring (PPM) is a specific task under the umbrella of Process Mining
that aims to predict several factors of a business process (eg, next activity prediction) based …