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A mostly pure-R implementation of the RAKE algorithm (Rose, S., Engel, D., Cramer, N. and Cowley, W. (2010) <doi:10.1002/9780470689646.ch1>), which can be used to extract keywords from documents without any training data.
Version: | 0.1.1 |
Depends: | R (≥ 3.1) |
Imports: | SnowballC, NLP, openNLP, utils |
Suggests: | testthat, knitr, rmarkdown |
Published: | 2017-11-02 |
DOI: | 10.32614/CRAN.package.slowraker |
Author: | Christopher Baker [aut, cre] |
Maintainer: | Christopher Baker <chriscrewbaker at gmail.com> |
BugReports: | https://github.com/crew102/slowraker/issues |
License: | MIT + file LICENSE |
URL: | https://crew102.github.io/slowraker/index.html |
NeedsCompilation: | no |
SystemRequirements: | Java (>= 5.0) |
Materials: | README |
CRAN checks: | slowraker results |
Reference manual: | slowraker.pdf |
Vignettes: |
FAQs Getting started |
Package source: | slowraker_0.1.1.tar.gz |
Windows binaries: | r-devel: slowraker_0.1.1.zip, r-release: slowraker_0.1.1.zip, r-oldrel: slowraker_0.1.1.zip |
macOS binaries: | r-release (arm64): slowraker_0.1.1.tgz, r-oldrel (arm64): slowraker_0.1.1.tgz, r-release (x86_64): slowraker_0.1.1.tgz, r-oldrel (x86_64): slowraker_0.1.1.tgz |
Old sources: | slowraker archive |
Reverse imports: | rapidraker |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.