A fast version of the Rapid Automatic Keyword Extraction (RAKE) algorithm
You can get the stable version on CRAN:
The development version of the package requires you to compile the latest Java source code in rapidrake-java, so it’s not as simple as making a call to
rapidraker is an R package that provides an implementation of the same keyword extraction algorihtm (RAKE) as
rapidraker::rapidrake() is written in Java, whereas
slowraker::slowrake() is written in R. This means that you can expect
rapidrake() to be considerably faster than
rapidrake() has the same arguments as
slowrake(), and both functions output the same type of object. You can therefore substitue
slowraker() without making any additional changes to your code.
library(slowraker) library(rapidraker) data("dog_pubs") rakelist <- rapidrake(txt = dog_pubs$abstract[1:5])
rapidrake() outputs a list of data frames. Each data frame contains the keywords that were extracted for an element of
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': 90 obs. of 4 variables: #> ..$ keyword:"current dog suitability assessments focus" ... #> ..$ freq :1 1 ... #> ..$ score :22 ... #> ..$ stem :"current dog suitabl assess focus" ... #> #...With 3 more data frames.
You can bind these data frames together using
rakedf <- rbind_rakelist(rakelist, doc_id = dog_pubs$doi[1:5]) head(rakedf, 5) #> doc_id keyword freq score stem #> 1 10.1371/journal.pone.0132820 assistance dog identification tags 1 10.8 assist dog identif tag #> 2 10.1371/journal.pone.0132820 animal control facilities 1 9.0 anim control facil #> 3 10.1371/journal.pone.0132820 emotional support animals 1 9.0 emot support anim #> 4 10.1371/journal.pone.0132820 small body sizes 1 9.0 small bodi size #> 5 10.1371/journal.pone.0132820 seemingly inappropriate dogs 1 7.9 seem inappropri dog
rapidraker, head over to