Abstract
Process mining is a new discipline aimed at constructing process models from event logs. Recently several methods for the discovery of transition systems from event logs were introduced. Considering these transition systems as finite state machines classical algorithms for deriving regular expressions can be applied. Regular expressions allow representing sequential process models in a hierarchical way, using sequence, choice, and iterative patterns. The aim of this work is to apply and tune an algorithm deriving regular expressions from transition systems within the process mining domain.
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Acknowledgment
This work was supported by the Basic Research Program at the National Research University Higher School of Economics and funded by the President Grant MK-4188.2018.9.
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Tarantsova, P.D., Kalenkova, A.A. (2018). Constructing Regular Expressions from Real-Life Event Logs. In: van der Aalst, W., et al. Analysis of Images, Social Networks and Texts. AIST 2018. Lecture Notes in Computer Science(), vol 11179. Springer, Cham. https://doi.org/10.1007/978-3-030-11027-7_26
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DOI: https://doi.org/10.1007/978-3-030-11027-7_26
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