quanteda (version 0.9.9-24)

similarity: compute similarities between documents and/or features

Description

Compute similarities between documents and/or features from a dfm. Uses the similarity measures defined in simil. See pr_DB for available distance measures, or how to create your own.

Usage

similarity(x, selection = NULL, n = NULL, margin = c("documents", "features"), method = "correlation", sorted = TRUE, normalize = FALSE)
"similarity"(x, selection = NULL, n = NULL, margin = c("documents", "features"), method = "correlation", sorted = TRUE, normalize = FALSE)
"as.matrix"(x, ...)

Arguments

x

a dfm object

selection

character or character vector of document names or feature labels from the dfm

n

the top n most similar items will be returned, sorted in descending order. If n is NULL, return all items.

margin

identifies the margin of the dfm on which similarity will be computed: documents for documents or features for word/term features.

method

a valid method for computing similarity from pr_DB

sorted

sort results in descending order if TRUE

normalize

a deprecated argument retained (temporarily) for legacy reasons. If you want to compute similarity on a "normalized" dfm objects (e.g. x), wrap it in weight(x, "relFreq").

...

unused

Value

a named list of the selection labels, with a sorted named vector of similarity measures.

Examples

# create a dfm from inaugural addresses from Reagan onwards
presDfm <- dfm(corpus_subset(data_corpus_inaugural, Year > 1980), stem = TRUE,
               remove = stopwords("english"))

# compute some document similarities
(tmp <- similarity(presDfm, margin = "documents"))
# output as a matrix
as.matrix(tmp)
# for specific comparisons
similarity(presDfm, "1985-Reagan", n = 5, margin = "documents")
similarity(presDfm, c("2009-Obama" , "2013-Obama"), n = 5, margin = "documents")
similarity(presDfm, c("2009-Obama" , "2013-Obama"), margin = "documents")
similarity(presDfm, c("2009-Obama" , "2013-Obama"), margin = "documents", method = "cosine")
similarity(presDfm, "2005-Bush", margin = "documents", method = "eJaccard", sorted = FALSE)

# compute some term similarities
similarity(presDfm, c("fair", "health", "terror"), method="cosine", margin = "features", 20)