Detecting and Understanding Branching Frequency Changes in Process Models
This work addresses the need for accurate detection of process changes in business process management, but it appears incremental as it builds on existing methods for analyzing exclusive choices.
The paper tackled the problem of detecting branching frequency changes in evolving business processes, proposing a method that uses event logs and process models to identify change points, and demonstrated its effectiveness on a real-life event log.
Business processes are continuously evolving in order to adapt to changes due to various factors. One type of process changes are branching frequency changes, which are related to changes in frequencies between different options when there is an exclusive choice. Existing methods either cannot detect such changes or cannot provide accurate and comprehensive results. In this paper, we propose a method which takes both event logs and process models as input and generates a choice sequence for each exclusive choice in the process model. The method then identifies change points based on the choice sequences. We evaluate our method on a real-life event log. Results show that our method can identify branching frequency changes in process models and provide comprehensive results to users.