Installation

You can get the stable version from CRAN:

install.packages("slowraker")

Or the development version from GitHub:

if (!"devtools" %in% rownames(installed.packages())) 
  install.packages("devtools")

devtools::install_github("crew102/slowraker")

Basic usage

There is one main function in the slowraker package - slowrake(). slowrake() extracts keywords from a vector of documents using the RAKE algorithm. This algorithm doesn’t require any training data, so it’s super easy to use:

library(slowraker)

data("dog_pubs")
rakelist <- slowrake(txt = dog_pubs$abstract[1:5])

slowrake() outputs a list of data frames. Each data frame contains the keywords that were extracted for a given document:

rakelist
#> 
#> # A rakelist containing 5 data frames:
#>  $ :'data.frame':    61 obs. of  4 variables:
#>   ..$ keyword:"assistance dog identification tags" ...
#>   ..$ freq   :1 1 ...
#>   ..$ score  :11 ...
#>   ..$ stem   :"assist dog identif tag" ...
#>  $ :'data.frame':    88 obs. of  4 variables:
#>   ..$ keyword:"current dog suitability assessments focus" ...
#>   ..$ freq   :1 1 ...
#>   ..$ score  :21 ...
#>   ..$ stem   :"current dog suitabl assess focu" ...
#> #...With 3 more data frames.

You can bind these data frames together using rbind_rakelist():

rbind_rakelist(rakelist, doc_id = dog_pubs$doi[1:5])

Learning more

One this site you will find: