most citedSaCoFa: Semantics-aware Control-flow Anonymization for Process Mining

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.DC20251 cited

ContinuumConductor : Decentralized Process Mining on the Edge-Cloud Continuum

Hendrik Reiter, Janick Edinger, Martin Kabierski +10

Process mining traditionally assumes centralized event data collection and analysis. However, modern Industrial Internet of Things systems increasingly operate over distributed, re…

cs.DB2025

Determining Window Sizes using Species Estimation for Accurate Process Mining over Streams

Christian Imenkamp, Martin Kabierski, Hendrik Reiter +3

Streaming process mining deals with the real-time analysis of event streams. A common approach for it is to adopt windowing mechanisms that select event data from a stream for subs…

cs.DB20212 cited

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…

cs.SE2021

Model Independent Error Bound Estimation for Conformance Checking Approximation

Mohammadreza Fani Sani, Martin Kabierski, Sebastiaan J. van Zelst +1

Conformance checking techniques allow us to quantify the correspondence of a process's execution, captured in event data, w.r.t., a reference process model. In this context, alignm…

cs.CR2021

Privacy-aware Process Performance Indicators: Framework and Release Mechanisms

Martin Kabierski, Stephan Fahrenkrog-Petersen, Matthias Weidlich

Process performance indicators (PPIs) are metrics to quantify the degree with which organizational goals defined based on business processes are fulfilled. They exploit the event l…