A first implementation of automated parsing of user stories, when used to defined functional requirements for operational research mathematical models. It allows reading user stories, splitting them on the who-what-why template, and classifying them according to the parts of the mathematical model that they represent. Also provides semantic grouping of stories, for project management purposes.
Version: 1.0.0 Depends: R (≥ 3.6.0) Imports: dplyr, stringr, tm, tibble, tidytext, topicmodels, rmarkdown, xlsx, knitr Suggests: reshape2, qpdf Published: 2020-07-07 DOI: 10.32614/CRAN.package.oRus Author: Melina Vidoni [aut, cre], Laura Cunico [aut] Maintainer: Melina Vidoni <melina.vidoni at rmit.edu.au> BugReports: https://github.com/melvidoni/oRus/issues License: GPL-3 URL: https://github.com/melvidoni/oRus NeedsCompilation: no Materials: README, NEWS CRAN checks: oRus results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=oRus to link to this page.
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