Publication Details
ESTHER ASARE
- NUGS-Anhui
- Information Security And Engineering (Phd)
- Anhui University Of Science And Technology
An Optimization Approach for Mining of Process Models with Infrequent Behaviors Integrating Data Flow and Control Flow 07 Sep 2021
scientific Programming
Discovery of effective infrequent sequences based on maximum probability path maximum probability path 07 Sep 2021
Taylor and Francis
Conformance Checking : Workflow of Hospitals and Workflow of Open-Source EMRs 07 Sep 2021
IEEE
2021 IEEE Access
14 Feb 2022 | 16:46
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.