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Automating Process Discovery Through Meta-learning

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Cooperative Information Systems (CoopIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13591))

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Abstract

Analyzing event logs generated during the execution of digital processes, organizations can monitor the behavior of dysfunctional or unspecified processes. For achieving the most refined results, high-quality and up-to-date process models are required. However, the selection of the proper process discovery algorithm is often addressed by human experts that can relate quality criteria, event logs behavior, and discovery techniques. Exploiting a meta-learning approach, we created a procedure that identifies the optimal discovery technique based on a user-defined balance of quality metrics. Our experiments exploited 1091 event logs representing extensive possible business process behaviors. Given a set of available algorithms, we obtained an F-score of 0.76 for recommending the discovery algorithm that maximizes quality criteria. Moreover, our method supports a more in-depth investigation of the process discovery problem by mapping log behavior and discovery techniques.

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Notes

  1. 1.

    https://github.com/gbrltv/process_discovery_meta_learning.

  2. 2.

    https://www.tf-pm.org/competitions-awards/discovery-contest.

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Author information

Authors and Affiliations

  1. Università degli Studi di Milano (UNIMI), Milan, Italy

    Gabriel Marques Tavares

  2. Università degli Studi di Trieste (UniTS), Trieste, Italy

    Sylvio Barbon Junior

  3. Khalifa University (KUST), Abu Dhabi, UAE

    Ernesto Damiani

Authors
  1. Gabriel Marques Tavares
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  2. Sylvio Barbon Junior
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  3. Ernesto Damiani
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Corresponding author

Correspondence to Gabriel Marques Tavares .

Editor information

Editors and Affiliations

  1. Telecom SudParis - Institut Polytechnique de Paris, Evry, France

    Mohamed Sellami

  2. University of Milan, Milan, Italy

    Paolo Ceravolo

  3. Utrecht University, Utrecht, The Netherlands

    Hajo A. Reijers

  4. Telecom SudParis - Institut Polytechnique de Paris, Evry, France

    Walid Gaaloul

  5. University of Lorraine, Vandoeuvre-les-Nancy, France

    Hervé Panetto

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Tavares, G.M., Junior, S.B., Damiani, E. (2022). Automating Process Discovery Through Meta-learning. In: Sellami, M., Ceravolo, P., Reijers, H.A., Gaaloul, W., Panetto, H. (eds) Cooperative Information Systems. CoopIS 2022. Lecture Notes in Computer Science, vol 13591. Springer, Cham. https://doi.org/10.1007/978-3-031-17834-4_12

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  • DOI: https://doi.org/10.1007/978-3-031-17834-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-17833-7

  • Online ISBN: 978-3-031-17834-4

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