Extracting Business Process Models Using Natural Language Processing (NLP) Techniques

This Doctoral Consortium paper discusses how NLP can be applied in the domain of BPM in order to automatically generate business process models from existing documentation within the organization. The main idea is that from the syntactic and grammatical structure of a sentence, the components of a business process model can be derived (i.e. activities, resources, tasks, patterns). The result would be a business process model depicted using BPMN - a dedicated business process modeling technique

[1]  Camille Ben Achour Writing and correcting textual scenarios for system design , 1998, Proceedings Ninth International Workshop on Database and Expert Systems Applications (Cat. No.98EX130).

[2]  Mathias Weske,et al.  Business Process Management , 2007, Springer Berlin Heidelberg.

[3]  Beatrice Santorini,et al.  Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.

[4]  Alexander Franz,et al.  Searching the Web by Voice , 2002, COLING.

[5]  Mathias Weske,et al.  Business Process Management: A Survey , 2003, Business Process Management.

[6]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[7]  James H. Martin,et al.  Speech and language processing: an introduction to natural language processing, computational linguistics, and speech recognition, 2nd Edition , 2000, Prentice Hall series in artificial intelligence.

[8]  Mathias Weske Business Process Management Architectures , 2012 .

[9]  Christopher D. Manning,et al.  Stanford typed dependencies manual , 2010 .