89 citations · 267 across the 13 of their papers we have counts for
13 papers
Process Analytics -- Data-driven Business Process Management
Matthias Stierle, Karsten Kraume, Martin Matzner
Data-driven analysis of business processes has a long tradition in research. However, recently the term of process mining is mostly used when referring to data-driven process analy…
Recent Advances in Data-Driven Business Process Management
Lars Ackermann, Martin Käppel, Laura Marcus +21
The rapid development of cutting-edge technologies, the increasing volume of data and also the availability and processability of new types of data sources has led to a paradigm sh…
Machine learning in business process management: A systematic literature review
Sven Weinzierl, Sandra Zilker, Sebastian Dunzer +1
Machine learning (ML) provides algorithms to create computer programs based on data without explicitly programming them. In business process management (BPM), ML applications are u…
A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis
Sandra Zilker, Sven Weinzierl, Mathias Kraus +2
Proactive analysis of patient pathways helps healthcare providers anticipate treatment-related risks, identify outcomes, and allocate resources. Machine learning (ML) can leverage…
Time Matters: Time-Aware LSTMs for Predictive Business Process Monitoring
An Nguyen, Srijeet Chatterjee, Sven Weinzierl +3
Predictive business process monitoring (PBPM) aims to predict future process behavior during ongoing process executions based on event log data. Especially, techniques for the next…
Prescriptive Business Process Monitoring for Recommending Next Best Actions
Sven Weinzierl, Sebastian Dunzer, Sandra Zilker +1
Predictive business process monitoring (PBPM) techniques predict future process behaviour based on historical event log data to improve operational business processes. Concerning t…
XNAP: Making LSTM-based Next Activity Predictions Explainable by Using LRP
Sven Weinzierl, Sandra Zilker, Jens Brunk +3
Predictive business process monitoring (PBPM) is a class of techniques designed to predict behaviour, such as next activities, in running traces. PBPM techniques aim to improve pro…
A Technique for Determining Relevance Scores of Process Activities using Graph-based Neural Networks
Matthias Stierle, Sven Weinzierl, Maximilian Harl +1
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 models…
Conformance checking: A state-of-the-art literature review
Sebastian Dunzer, Matthias Stierle, Martin Matzner +1
Conformance checking is a set of process mining functions that compare process instances with a given process model. It identifies deviations between the process instances' actual…
A Process Mining Software Comparison
Daniel Viner, Matthias Stierle, Martin Matzner
www.processmining-software.com is a dedicated website for process mining software comparison and was developed to give practitioners and researchers an overview of commercial tools…
A framework to evaluate the viability of robotic process automation for business process activities
Christian Wellmann, Matthias Stierle, Sebastian Dunzer +1
Robotic process automation (RPA) is a technology for centralized automation of business processes. RPA automates user interaction with graphical user interfaces, whereby it promise…
Cause vs. Effect in Context-Sensitive Prediction of Business Process Instances
Jens Brunk, Matthias Stierle, Leon Papke +3
Predicting undesirable events during the execution of a business process instance provides the process participants with an opportunity to intervene and keep the process aligned wi…
An empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs
S. Weinzierl, S. Zilker, J. Brunk +5
Researchers have proposed a variety of predictive business process monitoring (PBPM) techniques aiming to predict future process behaviour during the process execution. Especially,…