The pain: Upholding standards
Writing useful technical documentation is bound to some rules. Clear, correct and consistent use of terminology facilitates understanding, a standardized document structure helps in finding information faster and a sober and clear writing style helps anyone who values their time.
But how do you enforce a level of expected quality with a minimum, perhaps non-existing review process? Natural Language Processing (NLP) can help in several respects.
NLP can check how terminology is used
At the content level, Automatic Term Extraction in combination with other statistical methods can signal anomalies, and highlight suspicious use of certain terms within the context of the company. Feedback mechanisms can then assist the writers in performing quality control and documenting their understanding of certain terms to support future readers.
NLP helps create standardized templates
At the document level, the need for standardized templates to ease the flow of information often forces itself as a necessity as the amount of documents in a company grows. NLP can help in creating such a standard based on existing documentation using clustering techniques. Simultaneously it can standardize the legacy documentation to this newly created norm.
NLP can assist in improving writing style
And when it comes to style, automatic linguistic analyses can detect difficult passages and suggest where to simplify and make writing more sober.
[Check this other post to read about the added value of good documentation.]
Is this interesting for you?
Would you like to know more about how NLP can help you when writing and managing technical documentation? We are working on it! Please let us know and we will keep you up to date about our solutions. How?