Abstract
Two different types of processes can be distinguished: well-structured routine processes and agile processes where the control-flow cannot be predefined a priori. In a similar way, two modeling paradigms exist whereby procedural models are more adequate for routine processes and declarative models are more suitable for agile processes. Often business analysts are not confident in understanding process models; this holds even more for declarative process models. Natural language support for this kind of processes in order to improve their readability is desirable. In the work at hand we define a technique that transforms declarative models to intuitive natural language texts. Hereof, the approach focuses on content determination and structuring the output texts.
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Notes
- 1.
Our binary trees are object trees without optional associations. Hence, the meta model prevents information loss during serialization.
- 2.
Notations vary; we have chosen the notation used in [20].
- 3.
http://www.cogentex.com/technology/realpro/index.shtml, l.a.: March 13th, 2015.
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Ackermann, L., Schönig, S., Zeising, M., Jablonski, S. (2015). Natural Language Generation for Declarative Process Models. In: Barjis, J., Pergl, R., Babkin, E. (eds) Enterprise and Organizational Modeling and Simulation. EOMAS 2015. Lecture Notes in Business Information Processing, vol 231. Springer, Cham. https://doi.org/10.1007/978-3-319-24626-0_1
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