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Extracting Workflows from Natural Language Documents: A First Step

  • Leslie ShingEmail author
  • Allan WollaberEmail author
  • Satish ChikkagoudarEmail author
  • Joseph YuenEmail author
  • Paul AlvinoEmail author
  • Alexander ChambersEmail author
  • Tony AllardEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 342)

Abstract

Business process models are used to identify control-flow relationships of tasks extracted from information system event logs. These event logs may fail to capture critical tasks executed outside of regular logging environments, but such latent tasks may be inferred from unstructured natural language texts. This paper highlights two workflow discovery pipeline components which use NLP and sequence mining techniques to extract workflow candidates from such texts. We present our Event Labeling and Sequence Analysis (ELSA) prototype which implements these components, associated approach methodologies, and performance results of our algorithm against ground truth data from the Apache Software Foundation Public Email Archive.

Keywords

Workflow discovery Natural language Sequence mining 

Notes

Acknowledgment

This material is based upon work supported under Air Force Contract No. FA8721-05-C-0002 and/or FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the U. S. Air Force.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.MIT Lincoln LaboratoryLexingtonUSA
  2. 2.Naval Research LaboratoryWashington, D.C.USA
  3. 3.Commonwealth Bank of AustraliaSydneyAustralia
  4. 4.Defence Science and Technology GroupEdinburghAustralia

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