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 …
Multi-channel deep feature learning for intrusion detection
Networks had an increasing impact on modern life since network cybersecurity has become
an important research field. Several machine learning techniques have been developed to …
an important research field. Several machine learning techniques have been developed to …
Explainable artificial intelligence for process mining: A general overview and application of a novel local explanation approach for predictive process monitoring
N Mehdiyev, P Fettke - Interpretable artificial intelligence: A perspective of …, 2021 - Springer
The contemporary process-aware information systems possess the capabilities to record the
activities generated during the process execution. To leverage these process specific fine …
activities generated during the process execution. To leverage these process specific fine …
Digitally enabled supply chain integration through business and process analytics
F Bodendorf, S Dentler, J Franke - Industrial Marketing Management, 2023 - Elsevier
Supply chain integration (SCI) is the degree to which a manufacturer strategically
collaborates with its supply chain partners and collaboratively manages intra-and inter …
collaborates with its supply chain partners and collaboratively manages intra-and inter …
[HTML][HTML] Process data properties matter: Introducing gated convolutional neural networks (GCNN) and key-value-predict attention networks (KVP) for next event …
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 …
control processes at an early stage and reduce their action distance. In recent years …
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 …
Multi-task prediction method of business process based on BERT and transfer learning
H Chen, X Fang, H Fang - Knowledge-Based Systems, 2022 - Elsevier
Abstract Predictive Business Process Monitoring (PBPM) is one of the essential tasks in
Business Process Management (BPM). It aims to predict the future behavior of an ongoing …
Business Process Management (BPM). It aims to predict the future behavior of an ongoing …
Darwin: An online deep learning approach to handle concept drifts in predictive process monitoring
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 …
that aims to predict several factors of a business process (eg, next activity prediction) based …
A data-aware explainable deep learning approach for next activity prediction
The prediction of the next activity in a business process can be very useful in revealing
inefficiencies and take decisions to avoid undesired activities. In this direction, further …
inefficiencies and take decisions to avoid undesired activities. In this direction, further …