Supporting Process Model Validation through Natural Language Generation

Henrik Leopold, Jan Mendling, Artem Polyvyanyy

Publikation: Wissenschaftliche FachzeitschriftOriginalbeitrag in FachzeitschriftBegutachtung

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The design and development of process-aware information systems is often supported by specifying requirements
as business process models. Although this approach is generally accepted as an effective strategy, it remains a fundamental
challenge to adequately validate these models given the diverging skill set of domain experts and system analysts. As domain
experts often do not feel confident in judging the correctness and completeness of process models that system analysts create, the
validation often has to regress to a discourse using natural language. In order to support such a discourse appropriately, so-called
verbalization techniques have been defined for different types of conceptual models. However, there is currently no sophisticated
technique available that is capable of generating natural-looking text from process models. In this paper, we address this research
gap and propose a technique for generating natural language texts from business process models. A comparison with manually
created process descriptions demonstrates that the generated texts are superior in terms of completeness, structure, and linguistic
complexity. An evaluation with users further demonstrates that the texts are very understandable and effectively allow the reader
to infer the process model semantics. Hence, the generated texts represent a useful input for process model validation.
Seiten (von - bis)818 - 840
FachzeitschriftIEEE Transactions on Software Engineering
PublikationsstatusVeröffentlicht - 1 Dez. 2014