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Automated Business Process Discovery from Unstructured Natural-Language Documents

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Business Process Management Workshops (BPM 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 397))

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Abstract

Understanding the processes followed by organizations is important to ensure business outcomes are achieved in an optimal, efficient and compliant manner. Process mining techniques rely on the existence of structured event logs captured by process management systems. These systems are not always employed and may not capture all process steps, leaving out those that occur through emails and chat software or edits to documents and knowledge-management systems.

Here we present an algorithm for the automated extraction of processes from unstructured natural-language documents. Action and topic analysis is used to generate an event log, from which process models are mined using standard techniques. We show the algorithm is capable of generating consistent software-development processes from an Apache Camel email dataset.

DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited. This material is based upon work supported by the Under Secretary of Defense for Research and Engineering under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Under Secretary of Defense for Research and Engineering.

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Author information

Authors and Affiliations

  1. Defence Science and Technology, Edinburgh, SA, 5111, Australia

    Alexander J. Chambers, Amy M. Stringfellow, Ben B. Luo, Sophie J. Underwood, Tony G. Allard & Ian A. Johnston

  2. MIT Lincoln Laboratory, Lexington, MA, 02421, USA

    Sarah Brockman, Leslie Shing, Allan Wollaber & Courtland VanDam

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  1. Alexander J. Chambers
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  2. Amy M. Stringfellow
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  3. Ben B. Luo
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  4. Sophie J. Underwood
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  5. Tony G. Allard
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  6. Ian A. Johnston
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  7. Sarah Brockman
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  8. Leslie Shing
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  9. Allan Wollaber
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  10. Courtland VanDam
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Correspondence to Alexander J. Chambers .

Editor information

Editors and Affiliations

  1. Universidad de Sevilla, Seville, Spain

    Adela Del Río Ortega

  2. Kühne Logistics University, Hamburg, Germany

    Henrik Leopold

  3. Universidade do Estado do Rio de Janeiro – UERJ, Rio de Janeiro, Brazil

    Flávia Maria Santoro

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Chambers, A.J. et al. (2020). Automated Business Process Discovery from Unstructured Natural-Language Documents. In: Del Río Ortega, A., Leopold, H., Santoro, F.M. (eds) Business Process Management Workshops. BPM 2020. Lecture Notes in Business Information Processing, vol 397. Springer, Cham. https://doi.org/10.1007/978-3-030-66498-5_18

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  • DOI: https://doi.org/10.1007/978-3-030-66498-5_18

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