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Improving business process models using observed behavior


Joos C.A.M. Buijs, Marcello La Rosa, Hajo A. Reijers, Boudewijn van Dongen and Wil M.P. van der Aalst

TU Eindhoven


Queensland University of Technology


Process-aware information systems (PAISs) can be config- ured using a reference process model, which is typically obtained via expert interviews. Over time, however, contextual factors and system requirements may cause the operational process to start deviating from this reference model. While a reference model should ideally be updated to remain aligned with such changes, this is a costly and often neglected activity. We present a new process mining technique that automatically improves the reference model on the basis of the observed behavior as recorded in the event logs of a PAIS. We discuss how to balance the four basic quality dimensions for process mining (fitness, precision, sim- plicity and generalization) and a new dimension, namely the structural similarity between the reference model and the discovered model. We demonstrate the applicability of this technique using a real-life scenario from a Dutch municipality.

BibTeX Entry

    publisher        = {Springer},
    author           = {Buijs, Joos C.A.M. and La Rosa, Marcello and Reijers, Hajo A. and van Dongen, Boudewijn and van der
                        Aalst, Wil M.P.},
    month            = jun,
    editor           = {{Paolo Ceravolo, Philippe Cudre-Mauroux, Dragan Gasevic }},
    year             = {2013},
    keywords         = {process mining, process improvement, reference model, process model, automated process discovery},
    title            = {Improving Business Process Models using Observed Behavior},
    booktitle        = {nternational Symposium on Data-driven Process Discovery and Analysis (SIMPDA)},
    pages            = {TBA},
    address          = {Campione d'Italia, Italy}


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