Main Content

word2vec

Map word to embedding vector

所有的页面崩溃

Syntax

M = word2vec(emb,words)
M = word2vec(emb,words,'IgnoreCase',true)

Description

example

M= word2vec(emb,words)returns the embedding vectors ofwordsin the embeddingemb. If a word is not in the embedding vocabulary, then the function returns a row ofNaNs. The function, by default, is case sensitive.

M= word2vec(emb,words,'IgnoreCase',true)returns the embedding vectors ofwordsignoring case using any of the previous syntaxes. If multiple words in the embedding differ only in case, then the function returns the vector corresponding to one of them and does not return any particular vector.

Examples

collapse all

Open Live Script

Load a pretrained word embedding usingfastTextWordEmbedding. This function requires Text Analytics Toolbox™ Modelfor fastText English 16 Billion Token Word Embeddingsupport package. If this support package is not installed, then the function provides a download link.

emb = fastTextWordEmbedding
emb = wordEmbedding with properties: Dimension: 300 Vocabulary: [1×1000000 string]

Map the words "Italy", "Rome", and "Paris" to vectors usingword2vec.

italy = word2vec(emb,"Italy"); rome = word2vec(emb,"Rome"); paris = word2vec(emb,"Paris");

Map the vectoritaly - rome + paristo a word usingvec2word.

word = vec2word(emb,italy - rome + paris)
word = "France"

Input Arguments

collapse all

Input word embedding, specified as awordEmbeddingobject.

Input words, specified as a string vector, character vector, or cell array of character vectors. If you specifywordsas a character vector, then the function treats the argument as a single word.

Data Types:string|char|cell

Output Arguments

collapse all

Matrix of word embedding vectors.

See Also

|||||||

Topics

Introduced in R2017b

Text Analytics Toolbox Documentation

金宝app

Getting Started with Text Analytics in MATLAB

Getting Started with Text Analytics in MATLAB

Download now