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Weighing the Pros and Cons: Process Discovery with Negative Examples

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Business Process Management (BPM 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12875))

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Abstract

Contemporary process discovery methods take as inputs only positive examples of process executions, and so they are one-class classification algorithms. However, we have found negative examples to also be available in industry, hence we propose to treat process discovery as a binary classification problem. This approach opens the door to many well-established methods and metrics from machine learning, in particular to improve the distinction between what should and should not be allowed by the output model. Concretely, we (1) present a formalisation of process discovery as a binary classification problem; (2) provide cases with negative examples from industry, including real-life logs; (3) propose the Rejection Miner binary classification procedure, applicable to any process notation that has a suitable syntactic composition operator; and (4) apply this miner to the real world logs obtained from our industry partner, showing increased output model quality in terms of accuracy and model size.

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Notes

  1. 1.

    https://icpmconference.org/2019/process-discovery-contest/

    https://icpmconference.org/2020/process-discovery-contest/.

  2. 2.

    The name “\(\mathord {\text {F1}}\)” is used for a metric of unary miners defined like \(\mathord {\text {F1}}\) here, except using the escaping-edges notion of precision [8] en lieu of the \(\mathord {\text {PPV}}\).

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Copenhagen, Copenhagen, Denmark

    Tijs Slaats & Christoffer Olling Back

  2. IT University of Copenhagen, Copenhagen, Denmark

    Søren Debois

  3. DCR Solutions A/S, Copenhagen, Denmark

    Søren Debois

Authors
  1. Tijs Slaats
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  2. Søren Debois
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  3. Christoffer Olling Back
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Corresponding author

Correspondence to Tijs Slaats .

Editor information

Editors and Affiliations

  1. The University of Melbourne, Carlton, VIC, Australia

    Artem Polyvyanyy

  2. NICTA Queensland Research Lab, Queensland University of Technology, Brisbane, QLD, Australia

    Moe Thandar Wynn

  3. Ghent University, Ghent, Belgium

    Amy Van Looy

  4. Institut fur Datenbanken, Info System, Universitat Ulm, Ulm, Germany

    Manfred Reichert

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Slaats, T., Debois, S., Back, C.O. (2021). Weighing the Pros and Cons: Process Discovery with Negative Examples. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds) Business Process Management. BPM 2021. Lecture Notes in Computer Science(), vol 12875. Springer, Cham. https://doi.org/10.1007/978-3-030-85469-0_6

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  • DOI: https://doi.org/10.1007/978-3-030-85469-0_6

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