Detecting and Understanding Branching Frequency Changes in Process Models

TL;DR

This paper presents a new method for detecting branching frequency changes in business process models by analyzing event logs and process models to identify change points in exclusive choices.

Contribution

The paper introduces a novel approach that combines event logs and process models to accurately detect and analyze branching frequency changes in business processes.

Findings

Successfully detects branching frequency changes in real-life event logs

Provides comprehensive results for process analysis

Improves accuracy over existing methods

Abstract

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.