89 citations · 210 across the 6 of their papers we have counts for
9 papers
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…