Process Mining allows organizations to obtain actual business process models from event
logs (discovery), to compare the event log or the resulting process model in the discovery …

While a business process is most often executed following a normal path, anomalies may
sometimes arise and can be captured in event logs. Event log anomalies stem, for instance …

Nowadays, more and more process data are automatically recorded by information systems,
and made available in the form of event logs. Process mining techniques enable process …

The strong impulse to digitize processes and operations in companies and enterprises have
resulted in the creation and automatic recording of an increasingly large amount of process …

Process discovery algorithms extract process models from business process event logs.
Existing discovery algorithms require upfront filtering, or specific parameter input, to produce …

Conformance checking techniques let us find out to what degree a process model and real
execution data correspond to each other. In recent years, alignments have proven extremely …

One of the challenges in applying process mining algorithms on real event data, is the
presence of outlier behavior. Such behaviour often leads to complex, incomprehensible …

With Process discovery algorithms, we discover process models based on event data,
captured during the execution of business processes. The process discovery algorithms …

Process mining aims at gaining insights into business processes by analyzing the event
data that is generated and recorded during process execution. The vast majority of existing …

Various process mining techniques exist, eg, techniques that automatically discover a
descriptive model of the execution of a process, based on event data. Whereas the premise …