An Approach for Mining Multiple Types of Silent Transitions in Business Process

Abstract

The purpose of process discovery is to construct a process model based on business process execution data recorded in an event log. Many situations may lead to silent transitions that appeared in the process model, while the execution of silent transitions is not recorded in event logs. Therefore, mining silent transitions has been one of the difficult problems in process mining. Existing approaches have some limitations on discovering the silent transition in concurrent structures and may produce many redundant silent transitions which make discovered process model complicated. A novel approach to discover multiple types of silent transitions from an event log is presented in the paper. The basic behavior relationship between activity pairs based on the event log is used to construct the process model with silent transitions of and-gateway type and loop type. Meanwhile, the technique of behavior distance is proposed to discover silent transitions of skip type. Finally, the process model with multiple types of silent transitions is obtained. Experimental results show that the proposed approach can find multiple types of silent transitions correctly, and the number of redundant silent transitions is much less than the existing methods. Meanwhile, it significantly improves the F-measure of the model.

Keywords

• Behavior distance
• labeled Petri net
• process discovery
• silent transition