Artificial Intelligence Meets Process Mining: A Machine Learning Approach

Big Data as a buzzword of our times refers to increasing amounts of data that are being collected everywhere, and ways to deal with it. This collected data can be used and valuable knowledge can be extracted from it with the right methods, such as machine learning. Therefore, machine learning has become an influence on and gamechanger for many scientific disciplines, one of them being process mining. How and in what ways machine learning can be incorporated in process mining is the central question of this work. The thesis is conducted in cooperation with Nexontis Consulting GmbH. The contribution of this thesis is twofold. Firstly, a literature research is conducted to
analyze how machine learning methods can be employed in the domain of process mining. Relevant papers and approaches are summarized and introduced. As a second part of the thesis, several of these methods were implemented in Nexontis Consulting’s software as a first exploration. The potential of enhancing the software as a tool that combines process mining and machine learning was assessed and the findings
documented.