Redescription mining-based business process deviance analysis
Ahmeti E, Käppel M, Jablonski S (2024)
Publication Language: English
Publication Type: Journal article, Original article
Publication year: 2024
Journal
Book Volume: 23
Pages Range: 1421-1450
Journal Issue: 6
URI: https://link.springer.com/article/10.1007/s10270-024-01231-8
DOI: 10.1007/s10270-024-01231-8
Open Access Link: https://link.springer.com/article/10.1007/s10270-024-01231-8
Abstract
Business processes often deviate from their expected or desired behavior. Such deviations can be either positive or negative, depending on whether or not they lead to better process performance. Deviance mining addresses the problem of identifying such deviations and explaining why a process deviates. In this paper, we propose a novel approach to identify and explain the causes of deviant process executions based on the technique of redescription mining, which extracts knowledge in the form of logical rules. By analyzing, comparing, and filtering these rules, the reasons for the deviant behaviors of a business process are identified both in general and for particular process instances. Afterward, the results of this analysis are transformed into a concise and well-readable natural language text that can be used by business analysts and process owners to optimize processes in a reasoned manner. We evaluate our approach from different angles using four process models and provide some advice for further optimization.
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Germany (DE)How to cite
APA:
Ahmeti, E., Käppel, M., & Jablonski, S. (2024). Redescription mining-based business process deviance analysis. Software and Systems Modeling, 23(6), 1421-1450. https://doi.org/10.1007/s10270-024-01231-8
MLA:
Ahmeti, Engjëll, Martin Käppel, and Stefan Jablonski. "Redescription mining-based business process deviance analysis." Software and Systems Modeling 23.6 (2024): 1421-1450.
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