From low-level events to activities - a pattern-based approach


Mannhardt, Felix, De Leoni, Massimiliano, Reijers, Hajo A., van der Aalst, Wil M.P. & Toussaint, Pieter J. (2016). From low-level events to activities - a pattern-based approach. In P. Loos, M. La Rosa & O. Pastor (Eds.), Business Process Management (pp. 125-141). (Lecture Notes in Computer Science, No. 9850). Berlin: Springer. In Scopus Cited 12 times.

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Process mining techniques analyze processes based on event data. A crucial assumption for process analysis is that events correspond to occurrences of meaningful activities. Often, low-level events recorded by information systems do not directly correspond to these. Abstraction methods, which provide a mapping from the recorded events to activities recognizable by process workers, are needed. Existing supervised abstraction methods require a full model of the entire process as input and cannot handle noise. This paper proposes a supervised abstraction method based on behavioral activity patterns that capture domain knowledge on the relation between activities and events. Through an alignment between the activity patterns and the low-level event logs an abstracted event log is obtained. Events in the abstracted event log correspond to instantiations of recognizable activities. The method is evaluated with domain experts of a Norwegian hospital using an event log from their digital whiteboard system. The evaluation shows that state-of-the art process mining methods provide valuable insights on the usage of the system when using the abstracted event log, but fail when using the original lower level event log.