Automatic Generation of Technical Documentation
Ehud Reiter (CoGenTex, Ithaca, USA), Chris Mellish (University of, Edinburgh, UK), and John Levine (University of Edinburgh, UK)
TL;DR
This paper discusses the application of natural-language generation techniques to automatically produce technical documentation from knowledge bases, sharing insights from the IDAS project and industry feedback.
Contribution
It provides a detailed account of implementing NLG for technical documentation and lessons learned, aiding future research in this area.
Findings
NLG can effectively generate technical documentation from knowledge bases.
Industry feedback highlights practical benefits and challenges.
IDAS project offers valuable insights for future systems.
Abstract
Natural-language generation (NLG) techniques can be used to automatically produce technical documentation from a domain knowledge base and linguistic and contextual models. We discuss this application of NLG technology from both a technical and a usefulness (costs and benefits) perspective. This discussion is based largely on our experiences with the IDAS documentation-generation project, and the reactions various interested people from industry have had to IDAS. We hope that this summary of our experiences with IDAS and the lessons we have learned from it will be beneficial for other researchers who wish to build technical-documentation generation systems.
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Taxonomy
TopicsNatural Language Processing Techniques · Semantic Web and Ontologies · Software Engineering Research