DyLoPro : profiling the dynamics of event logs
- Author
- Brecht Wuyts, Hans Weytjens, Seppe vanden Broucke (UGent) and Jochen De Weerdt
- Organization
- Abstract
- Modern business processes are often characterized by continuous change, which can lead to bias in the results of process mining techniques that assume a static process. This bias is caused by concept drift, which can manifest in many forms and affect various process perspectives. Current research on concept drift in process mining has focused on drift detection techniques in the control-flow perspective, with limited capabilities for comprehensive dynamic profiling of event logs. To address this gap, this paper presents the DyLoPro framework, a generic approach that facilitates the exploration of event log dynamics over time using visual analytics. The framework caters to all types of event logs and allows for the exploration of event log dynamics from various process perspectives, both individually and combined with the performance perspective. Additionally, the framework is accompanied by an efficient and user-friendly Python library, rendering it a valuable instrument for both researchers and practitioners. A case study using large real-life event logs demonstrates the effectiveness of the framework.
- Keywords
- Process Mining, Event Logs, EDA, Concept Drift, Visual Analytics
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01HJB0SQT8W1QR6SHVKX5E7FW2
- MLA
- Wuyts, Brecht, et al. “DyLoPro : Profiling the Dynamics of Event Logs.” Business Process Management : 21st International Conference, BPM 2023, Proceedings, edited by Chiara Di Francescomarino et al., vol. 14159, Springer, 2023, pp. 146–62, doi:10.1007/978-3-031-41620-0_9.
- APA
- Wuyts, B., Weytjens, H., vanden Broucke, S., & De Weerdt, J. (2023). DyLoPro : profiling the dynamics of event logs. In C. Di Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business process management : 21st International Conference, BPM 2023, Proceedings (Vol. 14159, pp. 146–162). https://doi.org/10.1007/978-3-031-41620-0_9
- Chicago author-date
- Wuyts, Brecht, Hans Weytjens, Seppe vanden Broucke, and Jochen De Weerdt. 2023. “DyLoPro : Profiling the Dynamics of Event Logs.” In Business Process Management : 21st International Conference, BPM 2023, Proceedings, edited by Chiara Di Francescomarino, Andrea Burattin, Christian Janiesch, and Shazia Sadiq, 14159:146–62. Cham: Springer. https://doi.org/10.1007/978-3-031-41620-0_9.
- Chicago author-date (all authors)
- Wuyts, Brecht, Hans Weytjens, Seppe vanden Broucke, and Jochen De Weerdt. 2023. “DyLoPro : Profiling the Dynamics of Event Logs.” In Business Process Management : 21st International Conference, BPM 2023, Proceedings, ed by. Chiara Di Francescomarino, Andrea Burattin, Christian Janiesch, and Shazia Sadiq, 14159:146–162. Cham: Springer. doi:10.1007/978-3-031-41620-0_9.
- Vancouver
- 1.Wuyts B, Weytjens H, vanden Broucke S, De Weerdt J. DyLoPro : profiling the dynamics of event logs. In: Di Francescomarino C, Burattin A, Janiesch C, Sadiq S, editors. Business process management : 21st International Conference, BPM 2023, Proceedings. Cham: Springer; 2023. p. 146–62.
- IEEE
- [1]B. Wuyts, H. Weytjens, S. vanden Broucke, and J. De Weerdt, “DyLoPro : profiling the dynamics of event logs,” in Business process management : 21st International Conference, BPM 2023, Proceedings, Utrecht, The Netherlands, 2023, vol. 14159, pp. 146–162.
@inproceedings{01HJB0SQT8W1QR6SHVKX5E7FW2,
abstract = {{Modern business processes are often characterized by continuous change, which can lead to bias in the results of process mining techniques that assume a static process. This bias is caused by concept drift, which can manifest in many forms and affect various process perspectives. Current research on concept drift in process mining has focused on drift detection techniques in the control-flow perspective, with limited capabilities for comprehensive dynamic profiling of event logs. To address this gap, this paper presents the DyLoPro framework, a generic approach that facilitates the exploration of event log dynamics over time using visual analytics. The framework caters to all types of event logs and allows for the exploration of event log dynamics from various process perspectives, both individually and combined with the performance perspective. Additionally, the framework is accompanied by an efficient and user-friendly Python library, rendering it a valuable instrument for both researchers and practitioners. A case study using large real-life event logs demonstrates the effectiveness of the framework.}},
author = {{Wuyts, Brecht and Weytjens, Hans and vanden Broucke, Seppe and De Weerdt, Jochen}},
booktitle = {{Business process management : 21st International Conference, BPM 2023, Proceedings}},
editor = {{Di Francescomarino, Chiara and Burattin, Andrea and Janiesch, Christian and Sadiq, Shazia}},
isbn = {{9783031416194}},
issn = {{0302-9743}},
keywords = {{Process Mining,Event Logs,EDA,Concept Drift,Visual Analytics}},
language = {{eng}},
location = {{Utrecht, The Netherlands}},
pages = {{146--162}},
publisher = {{Springer}},
title = {{DyLoPro : profiling the dynamics of event logs}},
url = {{http://doi.org/10.1007/978-3-031-41620-0_9}},
volume = {{14159}},
year = {{2023}},
}
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