Matching of events and activities: an approach based on behavioral constraint satisfaction

Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during the execution of a process. This event data can be used to analyze the process using process mining techniques to discover the real process, measure conformance to a given process model, or to enhance existing models with performance information. While it is essential to map the produced events to activities of a given process model for conformance analysis and process model annotation, it is also an important step for the straightforward interpretation of process discovery results. In order to accomplish this mapping with minimal manual effort, we developed a semi-automatic approach that maps events to activities using the solution of a corresponding constraint satisfaction problem. The approach extracts behavioral profiles from both the log and the model to build constraints to efficiently reduce the number of possible mappings. The evaluation with an industry process model collection and simulated event logs demonstrates the effectiveness of the approach and its robustness towards non-conforming execution logs.