View source: R/3_1_textSimilarity.R
textSimilarity | R Documentation |
Compute the semantic similarity between two text variables.
textSimilarity(x, y, method = "cosine", center = TRUE, scale = FALSE)
x |
Word embeddings from textEmbed. |
y |
Word embeddings from textEmbed. |
method |
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. |
A vector comprising semantic similarity scores.
see textDistance
, textSimilarityNorm
library(dplyr)
similarity_scores <- textSimilarity(
x = word_embeddings_4$texts$harmonytext,
y = word_embeddings_4$texts$satisfactiontext
)
comment(similarity_scores)
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