95 citations · 315 across the 14 of their papers we have counts for
5 papers · 1 filter
Visualizing Trace Variants From Partially Ordered Event Data
Daniel Schuster, Lukas Schade, Sebastiaan J. van Zelst +1
Executing operational processes generates event data, which contain information on the executed process activities. Process mining techniques allow to systematically analyze event…
Freezing Sub-Models During Incremental Process Discovery: Extended Version
Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Process discovery aims to learn a process model from observed process behavior. From a user's perspective, most discovery algorithms work like a black box. Besides parameter tuning…
Removing Operational Friction Using Process Mining: Challenges Provided by the Internet of Production (IoP)
Wil van der Aalst, Tobias Brockhoff, Anahita Farhang Ghahfarokhi +3
Operational processes in production, logistics, material handling, maintenance, etc., are supported by cyber-physical systems combining hardware and software components. As a resul…
A Framework for Explainable Concept Drift Detection in Process Mining
Jan Niklas Adams, Sebastiaan J. van Zelst, Lara Quack +3
Rapidly changing business environments expose companies to high levels of uncertainty. This uncertainty manifests itself in significant changes that tend to occur over the lifetime…
Cortado---An Interactive Tool for Data-Driven Process Discovery and Modeling
Daniel Schuster, Sebastiaan J. van Zelst, Wil M. P. van der Aalst
Process mining aims to diagnose and improve operational processes. Process mining techniques allow analyzing the event data generated and recorded during the execution of (business…