associate: Find close terms in a textmatrix

In lsa: Latent Semantic Analysis

Find close terms in a textmatrix

Description

Returns those terms above a threshold close to the input term, sorted in descending order of their closeness. Alternatively, all terms and their closeness value can be returned sorted descending.

Usage

associate(textmatrix, term, measure = "cosine", threshold = 0.7)

Arguments

textmatrix	A document-term matrix.
term	The stimulus 'word'.
measure	The closeness measure to choose (Pearson, Spearman, Cosine)
threshold	Terms being closer than this threshold are going to be returned.

Details

Internally, a complete term-to-term similarity table is calculated, denoting the closeness (calculated with the specified measure) in its cells. All terms being close above this specified threshold are returned, sorted by their closeness value. Select a threshold of 0 to get all terms.

Value

termlist

A named vector of closeness values (terms as labels, sorted in descending order).

Author(s)

Fridolin Wild [e-mail]

See Also

textmatrix

Examples

# create some files
td = tempfile()
dir.create(td)
write( c("dog", "cat", "mouse"), file=paste(td, "D1", sep="/"))
write( c("hamster", "mouse", "sushi"), file=paste(td, "D2", sep="/"))
write( c("dog", "monster", "monster"), file=paste(td, "D3", sep="/"))
write( c("dog", "mouse", "dog"), file=paste(td, "D4", sep="/"))

# create matrices
myMatrix = textmatrix(td, minWordLength=1)
myLSAspace = lsa(myMatrix, dims=dimcalc_share()) 
myNewMatrix = as.textmatrix(myLSAspace) 

# calc associations for mouse
associate(myNewMatrix, "mouse")

# clean up
unlink(td, recursive=TRUE)

lsa documentation built on May 9, 2022, 9:10 a.m.