quanteda (version 1.5.2)

tokens_ngrams: Create ngrams and skipgrams from tokens

Description

Create a set of ngrams (tokens in sequence) from already tokenized text objects, with an optional skip argument to form skipgrams. Both the ngram length and the skip lengths take vectors of arguments to form multiple lengths or skips in one pass. Implemented in C++ for efficiency.

Usage

tokens_ngrams(x, n = 2L, skip = 0L, concatenator = "_")
char_ngrams(x, n = 2L, skip = 0L, concatenator = "_")
tokens_skipgrams(x, n, skip, concatenator = "_")

Arguments

x

a tokens object, or a character vector, or a list of characters

n

integer vector specifying the number of elements to be concatenated in each ngram. Each element of this vector will define a $n$ in the $n$-gram(s) that are produced.

skip

integer vector specifying the adjacency skip size for tokens forming the ngrams, default is 0 for only immediately neighbouring words. For skipgrams, skip can be a vector of integers, as the "classic" approach to forming skip-grams is to set skip = $k$ where $k$ is the distance for which $k$ or fewer skips are used to construct the $n$-gram. Thus a "4-skip-n-gram" defined as skip = 0:4 produces results that include 4 skips, 3 skips, 2 skips, 1 skip, and 0 skips (where 0 skips are typical n-grams formed from adjacent words). See Guthrie et al (2006).

concatenator

character for combining words, default is _ (underscore) character

Value

a tokens object consisting a list of character vectors of ngrams, one list element per text, or a character vector if called on a simple character vector

Details

Normally, these functions will be called through tokens(x, ngrams = , ...), but these functions are provided in case a user wants to perform lower-level ngram construction on tokenized texts.

tokens_skipgrams is a wrapper to tokens_ngrams that requires arguments to be supplied for both n and skip. For $k$-skip skipgrams, set skip to 0:$k$, in order to conform to the definition of skip-grams found in Guthrie et al (2006): A $k$ skip-gram is an ngram which is a superset of all ngrams and each $(k-i)$ skipgram until $(k-i)==0$ (which includes 0 skip-grams).

References

Guthrie, David, Ben Allison, Wei Liu, Louise Guthrie, and Yorick Wilks. 2006. "A Closer Look at Skip-Gram Modelling."

Examples

# NOT RUN {
# ngrams
tokens_ngrams(tokens(c("a b c d e", "c d e f g")), n = 2:3)

toks <- tokens(c(text1 = "the quick brown fox jumped over the lazy dog"))
tokens_ngrams(toks, n = 1:3)
tokens_ngrams(toks, n = c(2,4), concatenator = " ")
tokens_ngrams(toks, n = c(2,4), skip = 1, concatenator = " ")
# on character
char_ngrams(letters[1:3], n = 1:3)

# skipgrams
toks <- tokens("insurgents killed in ongoing fighting")
tokens_skipgrams(toks, n = 2, skip = 0:1, concatenator = " ") 
tokens_skipgrams(toks, n = 2, skip = 0:2, concatenator = " ") 
tokens_skipgrams(toks, n = 3, skip = 0:2, concatenator = " ")   
# }