12 citations · 12 across the 2 of their papers we have counts for
4 papers
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…
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…
Alignment Approximation for Process Trees
Daniel Schuster, Sebastiaan van Zelst, Wil M. P. van der Aalst
Comparing observed behavior (event data generated during process executions) with modeled behavior (process models), is an essential step in process mining analyses. Alignments are…
Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm
Daniel Schuster, Sebastiaan J. van Zelst
The execution of (business) processes generates valuable traces of event data in the information systems employed within companies. Recently, approaches for monitoring the correctn…