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Estimating Process Conformance by Trace Sampling and Result Approximation

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Business Process Management (BPM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11675))

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Abstract

The increasing volume of event data that is recorded by information systems during the execution of business processes creates manifold opportunities for process analytics. Specifically, conformance checking compares the behaviour as recorded by an information system to a model of desired behaviour. Unfortunately, state-of-the-art conformance checking algorithms scale exponentially in the size of both the event data and the model used as input. At the same time, event data used for analysis typically relates only to a certain interval of process execution, not the entire history. Given this inherent data incompleteness, we argue that an understanding of the overall conformance of process execution may be obtained by considering only a small fraction of a log. In this paper, we therefore present a statistical approach to ground conformance checking in trace sampling and conformance approximation. This approach reduces the runtime significantly, while still providing guarantees on the accuracy of the estimated conformance result. Comprehensive experiments with real-world and synthetic datasets illustrate that our approach speeds up state-of-the-art conformance checking algorithms by up to three orders of magnitude, while largely maintaining the analysis accuracy.

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Notes

  1. 1.

    https://github.com/Martin-Bauer/Conformance_Sketching.

  2. 2.

    While keeping the other parameter values stable at their respective defaults.

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Authors and Affiliations

  1. Department of Computer Science, Humboldt-Universität zu Berlin, Berlin, Germany

    Martin Bauer, Han van der Aa & Matthias Weidlich

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  1. Martin Bauer
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  2. Han van der Aa
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  3. Matthias Weidlich
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Correspondence to Han van der Aa .

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Editors and Affiliations

  1. University of Copenhagen, Copenhagen, Denmark

    Thomas Hildebrandt

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Boudewijn F. van Dongen

  3. University of Bayreuth, Bayreuth, Germany

    Maximilian Röglinger

  4. Vienna University of Economics and Business, Vienna, Austria

    Jan Mendling

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Bauer, M., van der Aa, H., Weidlich, M. (2019). Estimating Process Conformance by Trace Sampling and Result Approximation. In: Hildebrandt, T., van Dongen, B., Röglinger, M., Mendling, J. (eds) Business Process Management. BPM 2019. Lecture Notes in Computer Science(), vol 11675. Springer, Cham. https://doi.org/10.1007/978-3-030-26619-6_13

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  • DOI: https://doi.org/10.1007/978-3-030-26619-6_13

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