activity
20242026
collaborators

5 papers

cs.CV2026

All Eyes on the Workflow: Automated and Efficient Event Discovery from Video Streams

Marco Pegoraro, Jonas Seng, Dustin Heller +2

Disciplines such as business process management and process mining aid organizations by discovering insights about processes on the basis of recorded event data. However, an obstac…

cs.LG2025

ProReco: A Process Discovery Recommender System

Tsung-Hao Huang, Tarek Junied, Marco Pegoraro +1

Process discovery aims to automatically derive process models from historical execution data (event logs). While various process discovery algorithms have been proposed in the last…

cs.LG2025

Control-flow anomaly detection by process mining-based feature extraction and dimensionality reduction

Francesco Vitale, Marco Pegoraro, Wil M. P. van der Aalst +1

The business processes of organizations may deviate from normal control flow due to disruptive anomalies, including unknown, skipped, and wrongly-ordered activities. To identify th…

cs.DB2025

Applying Process Mining on Scientific Workflows: a Case Study on High Performance Computing Data

Zahra Sadeghibogar, Alessandro Berti, Marco Pegoraro +1

Computer-based scientific experiments are becoming increasingly data-intensive, necessitating the use of High-Performance Computing (HPC) clusters to handle large scientific workfl…

cs.DB2024

Ranking the Top-K Realizations of Stochastically Known Event Logs

Arvid Lepsien, Marco Pegoraro, Frederik Fonger +3

Various kinds of uncertainty can occur in event logs, e.g., due to flawed recording, data quality issues, or the use of probabilistic models for activity recognition. Stochasticall…