45 citations · 91 across the 17 of their papers we have counts for
8 papers · 1 filter
Let's Simply Count: Quantifying Distributional Similarity Between Activities in Event Data
Henrik Kirchmann, Stephan A. Fahrenkrog-Petersen, Xixi Lu +1
To obtain insights from event data, advanced process mining methods assess the similarity of activities to incorporate their semantic relations into the analysis. Here, distributio…
Cross-Organizational Analysis of Parliamentary Processes: A Case Study
Paul-Julius Hillmann, Stephan A. Fahrenkrog-Petersen, Jan Mendling
Process Mining has been widely adopted by businesses and has been shown to help organizations analyze and optimize their processes. However, so far, little attention has gone into…
Transforming Football Data into Object-centric Event Logs with Spatial Context Information
Vito Chan, Lennart Ebert, Paul-Julius Hillmann +3
Object-centric event logs expand the conventional single-case notion event log by considering multiple objects, allowing for the analysis of more complex and realistic process beha…
Control-flow Reconstruction Attacks on Business Process Models
Henrik Kirchmann, Stephan A. Fahrenkrog-Petersen, Felix Mannhardt +1
Process models may be automatically generated from event logs that contain as-is data of a business process. While such models generalize over the control-flow of specific, recorde…
Unraveling the Never-Ending Story of Lifecycles and Vitalizing Processes
Stephan A. Fahrenkrog-Petersen, Saimir Bala, Luise Pufahl +1
Business process management (BPM) has been widely used to discover, model, analyze, and optimize organizational processes. BPM looks at these processes with analysis techniques tha…
PMDG: Privacy for Multi-Perspective Process Mining through Data Generalization
Ryan Hildebrant, Stephan A. Fahrenkrog-Petersen, Matthias Weidlich +1
Anonymization of event logs facilitates process mining while protecting sensitive information of process stakeholders. Existing techniques, however, focus on the privatization of t…
SaCoFa: Semantics-aware Control-flow Anonymization for Process Mining
Stephan A. Fahrenkrog-Petersen, Martin Kabierski, Fabian Rösel +2
Privacy-preserving process mining enables the analysis of business processes using event logs, while giving guarantees on the protection of sensitive information on process stakeho…
PRIPEL: Privacy-Preserving Event Log Publishing Including Contextual Information
Stephan A. Fahrenkrog-Petersen, Han van der Aa, Matthias Weidlich
Event logs capture the execution of business processes in terms of executed activities and their execution context. Since logs contain potentially sensitive information about the i…