Information-preserving abstractions of event data in process mining

Process mining aims at obtaining information about processes by analysing their past executions in event logs, event streams, or databases. Discovering a process model from a finite amount of event data thereby has to correctly infer infinitely many unseen behaviours. Thereby, many process discovery techniques leverage abstractions on the finite event data to infer and preserve behavioural information of the underlying process. However, the...