Volgen
Martin Kabierski
Martin Kabierski
PhD Student, Humboldt-Unviersität zu Berlin
Geverifieerd e-mailadres voor hu-berlin.de
Titel
Geciteerd door
Geciteerd door
Jaar
How much event data is enough? A statistical framework for process discovery
M Bauer, A Senderovich, A Gal, L Grunske, M Weidlich
Advanced Information Systems Engineering: 30th International Conference …, 2018
382018
Estimating process conformance by trace sampling and result approximation
M Bauer, H Van der Aa, M Weidlich
Business Process Management: 17th International Conference, BPM 2019, Vienna …, 2019
292019
Elpaas: Event log privacy as a service
M Bauer, SA Fahrenkrog-Petersen, A Koschmider, F Mannhardt, ...
CEUR Workshop Proceedings [University Publisher], 2019
272019
Sampling and approximation techniques for efficient process conformance checking
M Bauer, H van der Aa, M Weidlich
Information Systems, 101666, 2020
192020
SaCoFa: Semantics-aware Control-flow Anonymization for Process Mining
SA Fahrenkog-Petersen, M Kabierski, F Rösel, H van der Aa, M Weidlich
2021 3rd International Conference on Process Mining (ICPM), 72-79, 2021
162021
Privacy-aware Process Performance Indicators: Framework and Release Mechanisms
M Kabierski, SA Fahrenkrog-Petersen, M Weidlich
International Conference on Advanced Information Systems Engineering, 19-36, 2021
132021
Semantics-aware mechanisms for control-flow anonymization in process mining
SA Fahrenkrog-Petersen, M Kabierski, H van der Aa, M Weidlich
Information Systems 114, 102169, 2023
62023
Sampling What Matters: Relevance-guided Sampling of Event Logs
M Kabierski, HL Nguyen, L Grunske, M Weidlich
2021 3rd International Conference on Process Mining (ICPM), 64-71, 2021
52021
Hiding in the forest: Privacy-preserving process performance indicators
M Kabierski, SA Fahrenkrog-Petersen, M Weidlich
Information Systems 112, 102127, 2023
32023
Model Independent Error Bound Estimation for Conformance Checking Approximation
MF Sani, M Kabierski, SJ van Zelst, WMP van der Aalst
arXiv preprint arXiv:2103.13315, 2021
32021
Addressing the Log Representativeness Problem using Species Discovery
M Kabierski, M Richter, M Weidlich
2023 5th International Conference on Process Mining (ICPM), 65-72, 2023
22023
Model-Independent Error Bound Estimation for Conformance Checking Approximation
M Fani Sani, M Kabierski, SJ van Zelst, WMP van der Aalst
International Conference on Business Process Management, 369-382, 2023
12023
Privacy-Preserving Process Mining with PM4Py
H Kirchmann, SA Fahrenkrog-Petersen, M Kabierski, H van der Aa, ...
ICPM Doctoral Consortium/Demo, 85-89, 2022
12022
Addressing the Log Representativeness Problem using Species Discovery (Extended Abstract) 2
M Kabierski, M Richter, M Weidlich
Enterprise Modeling and Information Systems Architecture (EMISA 2024), 43, 2024
2024
PaPPI: Privacy-aware Process Performance Indicators
M Kabierski, SA Fahrenkrog-Petersen, G Dittmann, M Weidlich
ICPM Doctoral Consortium/Demo, 113-117, 2022
2022
Representativeness of Event Data in Conformance Checking.
M Kabierski
BPM (PhD/Demos), 85-90, 2021
2021
Quantifying and Relating the Completeness and Diversity of Process Representations Using Species Estimation
M Kabierski, M Richter, M Weidlich
Available at SSRN 4790484, 0
Het systeem kan de bewerking nu niet uitvoeren. Probeer het later opnieuw.
Artikelen 1–17