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Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm

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Business Process Management (BPM 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12168))

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Abstract

The execution of (business) processes generates valuable tra-ces of event data in the information systems employed within companies. Recently, approaches for monitoring the correctness of the execution of running processes have been developed in the area of process mining, i.e., online conformance checking. The advantages of monitoring a process’ conformity during its execution are clear, i.e., deviations are detected as soon as they occur and countermeasures can immediately be initiated to reduce the possible negative effects caused by process deviations. Existing work in online conformance checking only allows for obtaining approximations of non-conformity, e.g., overestimating the actual severity of the deviation. In this paper, we present an exact, parameter-free, online conformance checking algorithm that computes conformance checking results on the fly. Our algorithm exploits the fact that the conformance checking problem can be reduced to a shortest path problem, by incrementally expanding the search space and reusing previously computed intermediate results. Our experiments show that our algorithm is able to outperform comparable state-of-the-art approximation algorithms.

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Notes

  1. 1.

    https://github.com/fit-daniel-schuster/online_process_monitoring_using_incremental_state-space_expansion_an_exact_algorithm.

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Authors and Affiliations

  1. Fraunhofer Institute for Applied Information Technology FIT, Sankt Augustin, Germany

    Daniel Schuster & Sebastiaan J. van Zelst

  2. RWTH Aachen University, Aachen, Germany

    Sebastiaan J. van Zelst

Authors
  1. Daniel Schuster
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  2. Sebastiaan J. van Zelst
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Corresponding author

Correspondence to Daniel Schuster .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Dirk Fahland

  2. FBK-irst, Trento, Italy

    Chiara Ghidini

  3. University of Münster, Münster, Germany

    Jörg Becker

  4. University of Tartu, Tartu, Estonia

    Marlon Dumas

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Schuster, D., van Zelst, S.J. (2020). Online Process Monitoring Using Incremental State-Space Expansion: An Exact Algorithm. In: Fahland, D., Ghidini, C., Becker, J., Dumas, M. (eds) Business Process Management. BPM 2020. Lecture Notes in Computer Science(), vol 12168. Springer, Cham. https://doi.org/10.1007/978-3-030-58666-9_9

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  • DOI: https://doi.org/10.1007/978-3-030-58666-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58665-2

  • Online ISBN: 978-3-030-58666-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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