Supporting Process Model Validation through Natural Language Generation

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...

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Vydáno v:IEEE transactions on software engineering Ročník 40; číslo 8; s. 818 - 840
Hlavní autoři: Leopold, Henrik, Mendling, Jan, Polyvyanyy, Artem
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.08.2014
IEEE Computer Society
Témata:
Adaptation models
Analytical models
Business
Completeness
Context
Context modeling
Descriptions
Information systems
Linguistics
Mathematical models
Natural language
Natural language processing
Natural languages
Programming languages
Software engineering
Strategy
Studies
Subject specialists
Systems design
Systems development
Texts
Unified modeling language
verbalization
natural language text generation
Business process model validation
ISSN:0098-5589, 1939-3520
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Shrnutí: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.
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ISSN:0098-5589
1939-3520
DOI:10.1109/TSE.2014.2327044