data mining - Finding 2 & 3 word Phrases Using R TM Package

Question

I am trying to find a code that actually works to find the most frequently used two and three word phrases in R text mining package (maybe there is another package for it that I do not know). I have been trying to use the tokenizer, but seem to have no luck.

If you worked on a similar situation in the past, could you post a code that is tested and actually works? Thank you so much!

Answer 1

You can pass in a custom tokenizing function to tm's DocumentTermMatrix function, so if you have package tau installed it's fairly straightforward.

library(tm); library(tau);

tokenize_ngrams <- function(x, n=3) return(rownames(as.data.frame(unclass(textcnt(x,method="string",n=n)))))

texts <- c("This is the first document.", "This is the second file.", "This is the third text.")
corpus <- Corpus(VectorSource(texts))
matrix <- DocumentTermMatrix(corpus,control=list(tokenize=tokenize_ngrams))

Where n in the tokenize_ngrams function is the number of words per phrase. This feature is also implemented in package RTextTools, which further simplifies things.

library(RTextTools)
texts <- c("This is the first document.", "This is the second file.", "This is the third text.")
matrix <- create_matrix(texts,ngramLength=3)

This returns a class of DocumentTermMatrix for use with package tm.