Application of Process Mining in Intelligent Process Support

Abstract

In last decades, systems started to be more and more process-oriented. The shift to process-oriented systems was motivated by the idea of supporting systems of the daily business and by the idea to shift the knowledge about operations that could be described as processes from humans to systems. The knowledge about the processes and their enactment was partially transferred to the systems. This thesis presents research in the area of intelligent process support with the use of process mining methods. In detail, the first part of the thesis presents the new approach of business process analysis using sequence alignment methods in the process mining area. The second part introduces the new approach for software process prediction based on use case with use of machine learning methods. In the third part of thesis is proposal of the overall methodology, which provides a connection between process mining and process modeling approaches.