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Discovering Block-Structured Process Models from Incomplete Event Logs

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Application and Theory of Petri Nets and Concurrency (PETRI NETS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8489))

Abstract

One of the main challenges in process mining is to discover a process model describing observed behaviour in the best possible manner. Since event logs only contain example behaviour and one cannot assume to have seen all possible process executions, process discovery techniques need to be able to handle incompleteness. In this paper, we study the effects of such incomplete logs on process discovery. We analyse the impact of incompleteness of logs on behavioural relations, which are abstractions often used by process discovery techniques. We introduce probabilistic behavioural relations that are less sensitive to incompleteness, and exploit these relations to provide a more robust process discovery algorithm. We prove this algorithm to be able to rediscover a model of the original system. Furthermore, we show in experiments that our approach even rediscovers models from incomplete event logs that are much smaller than required by other process discovery algorithms.

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Authors and Affiliations

  1. Eindhoven University of Technology, The Netherlands

    Sander J. J. Leemans, Dirk Fahland & Wil M. P. van der Aalst

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  1. Sander J. J. Leemans
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  2. Dirk Fahland
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  3. Wil M. P. van der Aalst
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Editors and Affiliations

  1. Department of Computer Science, Iowa State University, 226 Atanasoff Hall, 50011, Ames, IA, USA

    Gianfranco Ciardo

  2. DTU Compute, Technical University of Denmark, Richard Pedersens Plads, 2800 Kgs., Lyngby, Denmark

    Ekkart Kindler

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Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P. (2014). Discovering Block-Structured Process Models from Incomplete Event Logs. In: Ciardo, G., Kindler, E. (eds) Application and Theory of Petri Nets and Concurrency. PETRI NETS 2014. Lecture Notes in Computer Science, vol 8489. Springer, Cham. https://doi.org/10.1007/978-3-319-07734-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-07734-5_6

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07733-8

  • Online ISBN: 978-3-319-07734-5

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