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

F. Mannhardt, M. de Leoni, H.A. Reijers, W.M.P. van der Aalst, P.J. Toussaint

    Research output: Book/ReportReportAcademic

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    Abstract

    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.
    Original languageEnglish
    PublisherBPMcenter. org
    Number of pages18
    Publication statusPublished - 2016

    Publication series

    NameBPM Center Report
    Volume16-02

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