knitr::opts_chunk$set( collapse = TRUE, comment = "#>", progress = FALSE, error = FALSE, message = FALSE, warning = FALSE ) options(digits = 2)
A fast version of the Rapid Automatic Keyword Extraction (RAKE) algorithm
You can get the stable version on CRAN:
The development version of the package requires you to compile the latest Java source code in rapidrake-java, so installing it is not as simple as making a call to
rapidraker is an R package that provides an implementation of the same keyword extraction algorihtm (RAKE) as
rapidraker::rapidrake() is written in Java, whereas
slowraker::slowrake() is written in R. This means that you can expect
rapidrake() to be considerably faster than
rapidrake() has the same arguments as
slowrake(), and both functions output the same type of object. You can therefore substitue
slowraker() without making any additional changes to your code.
library(slowraker) library(rapidraker) data("dog_pubs") rakelist <- rapidrake(txt = dog_pubs$abstract[1:5])
# Note, we have to split the README.Rmd up like this so that it doesn't print # the progress bar. library(slowraker) library(rapidraker) options(width = 100, digits = 2) data("dog_pubs") rakelist <- rapidrake(txt = dog_pubs$abstract[1:5])
rapidrake() outputs a list of data frames. Each data frame contains the keywords that were extracted for an element of
You can bind these data frames together using
rakedf <- rbind_rakelist(rakelist, doc_id = dog_pubs$doi[1:5]) head(rakedf, 5)
rapidraker, head over to
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