Lu, Y.; Chen, Q.; Poon, S.K. Detecting Branching Condition Changes in Process Models. Preprints2021, 2021090191. https://doi.org/10.20944/preprints202109.0191.v1
APA Style
Lu, Y., Chen, Q., & Poon, S.K. (2021). Detecting Branching Condition Changes in Process Models. Preprints. https://doi.org/10.20944/preprints202109.0191.v1
Chicago/Turabian Style
Lu, Y., Qifan Chen and Simon K. Poon. 2021 "Detecting Branching Condition Changes in Process Models" Preprints. https://doi.org/10.20944/preprints202109.0191.v1
Abstract
Business processes are continuously evolving in order to adapt to changes due to various factors. One important process drift perspective yet to be investigated is the detection of branching condition changes in the process model. None of the existing process drift detection methods focus on detecting changes of branching conditions in process models. Existing branching condition detection methods do not take changes within the process into account, hence results are inadequate to represent the changes of decision criteria of the process. In this paper, we present a method which can detect branching condition changes in process models. The method takes both process models and event logs as input, and translates event logs into decision sequences for change points detection. The proposed method is evaluated by simulated event logs.
Keywords
Process science; Data science; Concept drift detection and Branching frequency changes
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.