word2vec is a Go package which provides functions for querying word2vec models (see https://code.google.com/p/word2vec). Any binary word2vec model file can be loaded and queried.
If you haven't setup Go before, you need to first set a GOPATH (see https://golang.org/doc/code.html#GOPATH).
To fetch and build the code:
$ go get github.com/sajari/word2vec/...
This will build the command line tools (in particular word-calc, word-server, word-client) into $GOPATH/bin (assumed to be in your PATH already).
The word-calc tool is a quick way to perform basic word calculations on a word2vec model. For instance: vec(king) - vec(man) + vec(woman) would be equivalent to:
$ word-calc -model /path/to/model.bin -add king,woman -sub man
See word-calc -h for full more details. Note that word-calc first loads the model every time, and so can appear to be quite slow. Use word-server and word-client to get better performance when running multiple queries on the same model.
The word-server tool (see cmd/word-server) creates an HTTP server which wraps a word2vec model which can be queried from Go using a Client, or using the word-client tool (see cmd/word-client).
$ word-server -model /path/to/model.bin -listen localhost:1234
A simple code example using Client:
c := word2vec.Client{Addr: "localhost:1234"}
// Create an expression.
expr := word2vec.Expr{}
expr.Add(1, "king")
expr.Add(-1, "man")
expr.Add(1, "woman")
// Find the most similar result by cosine similarity.
matches, err := c.CosN(expr, 1)
if err != nil {
log.Fatalf("error evaluating cosine similarity: %v", err)
}Alternatively you can interact with a word2vec model directly in your code:
// Load the model from an io.Reader (i.e. a file).
model, err := word2vec.FromReader(r)
if err != nil {
log.Fatalf("error loading model: %v", err)
}
// Create an expression.
expr := word2vec.Expr{}
expr.Add(1, "king")
expr.Add(-1, "man")
expr.Add(1, "woman")
// Find the most similar result by cosine similarity.
matches, err := model.CosN(expr, 1)
if err != nil {
log.Fatalf("error evaluating cosine similarity: %v", err)
}