On the Contextualization of Event-Activity Mappings

Postprint version of original article. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-030-11641-5_35Event log files are used as input to any process mining algorithm. A main assumption of process mining is that each event has been assigned to a distinct process activity already. However, such mapping of events to activities is a considerable challenge. The current status-quo is that approaches indicate only likelihoods of mappings, since there is often more than one possible solution. To increase the quality of event to activity mappings this paper derives a contextualization for event-activity mappings and argues for a stronger consideration of contextual factors. Based on a literature review, the paper provides a framework for classifying context factors for event-activity mappings. We aim to apply this framework to improve the accuracy of event-activity mappings and, thereby, process mining results in scenarios with low-level events.acceptedVersio

On the Contextualization of Event-Activity Mappings

Event log files are used as input to any process mining algorithm. A main assumption of process mining is that each event has been assigned to a distinct process activity already. However, such mapping of events to activities is a considerable challenge. The current status-quo is that approaches indicate only likelihoods of mappings, since there is often more than one possible solution. To increase the quality of event to activity mappings this paper derives a contextualization for event-activity mappings and argues for a stronger consideration of contextual factors. Based on a literature review, the paper provides a framework for classifying context factors for event-activity mappings. We aim to apply this framework to improve the accuracy of event-activity mappings and, thereby, process mining results in scenarios with low-level events