Mining Process Models from Natural Language Text: A State-of-the-Art Analysis

Maximilian Riefer, Simon Felix Ternis, Tom Thaler

In: Tagungsband der Multikonferenz Wirtschaftsinformatik. Multikonferenz Wirtschaftsinformatik (MKWI-16) March 9-11 Illmenau Germany Universität Illmenau 3/2016.


Workflow projects are time-consuming processes. They include the knowledge extraction and the creation of process models. The necessary information is often available as textual resources. Therefore, process model mining from natural language text has been a research area of growing interest. This paper gives an overview of the current state-of-the-art in text-to-model mining. For this purpose, different approaches focusing on business process models are presented, analyzed and compared against each other on a theoretical and technical level. The resulting overview covers both advantages and disadvantages of current techniques. This should establish a sturdy basis on which further research can be conducted.

RieferTernisThaler2016_Text2ModelMining.pdf (pdf, 449 KB)

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence