cosineSimilarity: Cosine Similarity

In bmschmidt/wordVectors: Tools for creating and analyzing vector-space models of texts

Cosine Similarity

Description

Calculate the cosine similarity of two matrices or a matrix and a vector.

Usage

cosineSimilarity(x, y)

Arguments

x	A matrix or VectorSpaceModel object
y	A vector, matrix or VectorSpaceModel object. Vector inputs are coerced to single-row matrices; y must have the same number of dimensions as x.

Value

A matrix. Rows correspond to entries in x; columns to entries in y.

Examples

# Inspect the similarity of several academic disciplines by hand.
subjects = demo_vectors[[c("history","literature","biology","math","stats"),average=FALSE]]
similarities = cosineSimilarity(subjects,subjects)

# Use 'closest_to' to build up a large list of similar words to a seed set.
subjects = demo_vectors[[c("history","literature","biology","math","stats"),average=TRUE]]
new_subject_list = closest_to(demo_vectors,subjects,20)
new_subjects = demo_vectors[[new_subject_list$word,average=FALSE]]

# Plot the cosineDistance of these as a dendrogram.
plot(hclust(as.dist(cosineDist(new_subjects,new_subjects))))

bmschmidt/wordVectors documentation built on June 2, 2022, 3:53 p.m.