News

Assistant Professor Dr. Stefan Schönig gave a talk about his ongoing research in terms of multi-perspective declarative process mining. The title of the given talk: "Event Log-Analyse durch multi-perspektivisches, deklaratives Process Mining".

Abstract of the given talk:

Process discovery is one of the main branches of process mining that allows the user to build a process model representing the process behavior as recorded in the logs. Standard process discovery techniques produce as output a procedural process model (e.g., a Petri net). Recently, several approaches have been developed to derive declarative process models from logs and have been proven to be more suitable to analyze processes working in environments that are less stable and

predictable. However, a large part of these techniques are focused on the analysis of the control flow perspective of a business process. Therefore, one of the challenges still open in this field is the development of techniques for the analysis of business processes also from other perspectives, like data, time, and resources. In this research talk, an approach for the discovery of multi-perspective declarative process models from event logs is presented that allows the user to discover declarative models taking into consideration all the information an event log can provide.