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Towards an Empirical Evaluation of Imperative and Declarative Process Mining

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Advances in Conceptual Modeling (ER 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11158))

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Abstract

Process modelling notations fall in two broad categories: declarative notations, which specify the rules governing a process; and imperative notations, which specify the flows admitted by a process. We outline an empirical approach to addressing the question of whether certain process logs are better suited for mining to imperative than declarative notations. We plan to attack this question by applying a flagship imperative and declarative miner to a standard collection of process logs, then evaluate the quality of the output models w.r.t. the standard model metrics of precision and generalisation. This approach requires perfect fitness of the output model, which substantially narrows the field of available miners; possible candidates include Inductive Miner and MINERful. With the metrics in hand, we propose to statistically evaluate the hypotheses that (1) one miner consistently outperforms the other on one of the metrics, and (2) there exist subsets of logs more suitable for imperative respectively declarative mining.

T. Slaats—This work is supported by the Hybrid Business Process Management Technologies project (DFF-6111-00337) funded by the Danish Council for Independent Research, and the EcoKnow project (7050-00034A) funded by the Innovation Foundation.

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Notes

  1. 1.

    http://data.4tu.nl/repository/collection:event_logs_real.

  2. 2.

    Available at: https://bitbucket.org/coback/qmpm.

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Authors and Affiliations

  1. Department of Computer Science, University of Copenhagen, Emil Holms Kanal 6, 2300, Copenhagen S, Denmark

    Christoffer Olling Back & Tijs Slaats

  2. Department of Computer Science, IT University of Copenhagen, Rued Langgaards Vej 7, 2300, Copenhagen S, Denmark

    Søren Debois

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

Correspondence to Christoffer Olling Back .

Editor information

Editors and Affiliations

  1. University of British Columbia, Vancouver, BC, Canada

    Carson Woo

  2. University of Helsinki, Helsinki, Finland

    Jiaheng Lu

  3. Northwestern Polytechnical University, Xian, China

    Zhanhuai Li

  4. Department of Computer Science, National University of Singapore, Singapore, Singapore

    Tok Wang Ling

  5. Department of Computer Science and Technology, Tsinghua University, Beijing, Beijing, China

    Guoliang Li

  6. National University of Singapore, Singapore, Singapore

    Mong Li Lee

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Back, C.O., Debois, S., Slaats, T. (2018). Towards an Empirical Evaluation of Imperative and Declarative Process Mining. In: Woo, C., Lu, J., Li, Z., Ling, T., Li, G., Lee, M. (eds) Advances in Conceptual Modeling. ER 2018. Lecture Notes in Computer Science(), vol 11158. Springer, Cham. https://doi.org/10.1007/978-3-030-01391-2_24

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  • DOI: https://doi.org/10.1007/978-3-030-01391-2_24

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