tokenizers: Split texts into tokens

In ropensci/textreuse: Detect Text Reuse and Document Similarity

Description

These functions each turn a text into tokens. The tokenize_ngrams functions returns shingled n-grams.

Usage

tokenize_words(string, lowercase = TRUE)

tokenize_sentences(string, lowercase = TRUE)

tokenize_ngrams(string, lowercase = TRUE, n = 3)

tokenize_skip_ngrams(string, lowercase = TRUE, n = 3, k = 1)

Arguments

string	A character vector of length 1 to be tokenized.
lowercase	Should the tokens be made lower case?
n	For n-gram tokenizers, the number of words in each n-gram.
k	For the skip n-gram tokenizer, the maximum skip distance between words. The function will compute all skip n-grams between 0 and k.

Details

These functions will strip all punctuation.

Value

A character vector containing the tokens.

Examples

dylan <- "How many roads must a man walk down? The answer is blowin' in the wind."
tokenize_words(dylan)
tokenize_sentences(dylan)
tokenize_ngrams(dylan, n = 2)
tokenize_skip_ngrams(dylan, n = 3, k = 2)

ropensci/textreuse documentation built on May 19, 2020, 7:40 a.m.