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 …
Creating business value with process mining
Abstract Information systems research has a long-standing interest in how organizations
gain value through information technology. In this article, we investigate a business process …
gain value through information technology. In this article, we investigate a business process …
Predictive business process monitoring with LSTM neural networks
Predictive business process monitoring methods exploit logs of completed cases of a
process in order to make predictions about running cases thereof. Existing methods in this …
process in order to make predictions about running cases thereof. Existing methods in this …
[PDF][PDF] Predictive process monitoring
C Di Francescomarino, C Ghidini - Process Mining Handbook, 2022 - library.oapen.org
Predictive Process Monitoring [29] is a branch of process mining that aims at predicting the
future of an ongoing (uncompleted) process execution. Typical examples of predictions of …
future of an ongoing (uncompleted) process execution. Typical examples of predictions of …
Learning accurate LSTM models of business processes
Deep learning techniques have recently found applications in the field of predictive business
process monitoring. These techniques allow us to predict, among other things, what will be …
process monitoring. These techniques allow us to predict, among other things, what will be …
Predictive process monitoring methods: Which one suits me best?
Predictive process monitoring has recently gained traction in academia and is maturing also
in companies. However, with the growing body of research, it might be daunting for data …
in companies. However, with the growing body of research, it might be daunting for data …
Machine learning in business process monitoring: a comparison of deep learning and classical approaches used for outcome prediction
W Kratsch, J Manderscheid, M Röglinger… - Business & Information …, 2021 - Springer
Predictive process monitoring aims at forecasting the behavior, performance, and outcomes
of business processes at runtime. It helps identify problems before they occur and re …
of business processes at runtime. It helps identify problems before they occur and re …
Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring
Predictive business process monitoring methods exploit historical process execution logs to
generate predictions about running instances (called cases) of a business process, such as …
generate predictions about running instances (called cases) of a business process, such as …
Intra and inter-case features in predictive process monitoring: A tale of two dimensions
A Senderovich, C Di Francescomarino… - … Conference, BPM 2017 …, 2017 - Springer
Predictive process monitoring is concerned with predicting measures of interest for a
running case (eg, a business outcome or the remaining time) based on historical event logs …
running case (eg, a business outcome or the remaining time) based on historical event logs …
A deep learning approach for predicting process behaviour at runtime
Predicting the final state of a running process, the remaining time to completion or the next
activity of a running process are important aspects of runtime process management …
activity of a running process are important aspects of runtime process management …