This matrix is a typical example of a term-term DSM co-occurrence matrix, derived from the English Wikipedia. It is available as a plain matrix in dense representation, and as a DSM object including marginal frequency data.
DSM_TermTermMatrix is a numeric matrix with 7 rows and 7 columns.
Rows represent the target nouns cat, dog, animal, time, reason, cause, effect.
Columns specify co-occurrence frequencies of these nouns with the words breed, tail, feed, kill, important, explain and likely in articles of the English Wikipedia. Co-occurring words must appear within a distance of at most two word tokens of each other.
DSM_TermTerm is an object of class
dsm based on the same co-occurrence matrix, but with additional information on marginal frequencies of the target and feature terms.
This matrix/DSM describes the same target terms as the term-context matrix
DSM_TermContextMatrix and corresponding DSM object
DSM_TermTermMatrix["time", ] # row vector for target noun "time" all.equal(DSM_TermTermMatrix, head(DSM_TermTerm, Inf)) ## Not run: plot(hclust(dist.matrix(DSM_TermTermMatrix, as.dist=TRUE))) ## End(Not run)
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