Matching of events and activities – an approach using declarative modeling constraints

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. Mapping the produced events to activities of a given process model is essential for conformance checking, annotation and understanding of process mining results. In order to accomplish this mapping with low manual effort, we developed a semiautomatic approach that maps events to activities using the solution of a corresponding constraint satisfaction problem. The approach extracts Declare constraints from both the log and the model to build matching 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