Leveraging Desirable and Undesirable Event Logs in Process Mining Tasks

Abstract

Traditional process mining techniques utilize one event log as input to offer organizational insights. In many applications, information regarding undesirable process aspects may exist. However, the literature lacks a comprehensive overview of their integration into process mining tasks. In our paper, we explore leveraging data from both desirable and undesirable event logs to augment existing process mining tasks and develop innovative applications. Our aim is to systematically outline the potential for enhancements in this realm.