Return the top n (by default n = 10) words similar to word.

cosine_similar_words(model, word, n = 10L)

# S3 method for wordvectors
cosine_similar_words(model, word, n = 10L)

Arguments

model

A model as returned by word_vectors.

word

The word to extract.

n

Number of neightbours to return.

Examples

# NOT RUN {
# setup word2vec Julia dependency
setup_word2vec()

# sample corpus
data("macbeth", package = "word2vec.r")

# train model
model_path <- word2vec(macbeth)

# get word vectors
model <- word_vectors(model_path)

# words similar to macbeth
cosine_similar_words(model, "macbeth", 20L)
# }