textSimilarityMatrix {text} | R Documentation |
Compute semantic similarity scores between all combinations in a word embedding
Description
Compute semantic similarity scores between all combinations in a word embedding
Usage
textSimilarityMatrix(x, method = "cosine", center = TRUE, scale = FALSE)
Arguments
x |
Word embeddings from textEmbed. |
method |
(character) Character string describing type of measure to be computed. Default is "cosine" (see also "spearmen", "pearson" as well as measures from textDistance() (which here is computed as 1 - textDistance) including "euclidean", "maximum", "manhattan", "canberra", "binary" and "minkowski"). |
center |
(boolean; from base::scale) If center is TRUE then centering is done by subtracting the column means (omitting NAs) of x from their corresponding columns, and if center is FALSE, no centering is done. |
scale |
(boolean; from base::scale) If scale is TRUE then scaling is done by dividing the (centered) columns of x by their standard deviations if center is TRUE, and the root mean square otherwise. |
Value
A matrix of semantic similarity scores
See Also
Examples
similarity_scores <- textSimilarityMatrix(word_embeddings_4$texts$harmonytext[1:3, ])
round(similarity_scores, 3)