How to find the closest word to a vector using word2vec

Question

I have just started using Word2vec and I was wondering how can we find the closest word to a vector suppose. I have this vector which is the average vector for a set of vectors

Answer 1

Alternatively, model.wv.similar_by_vector(vector, topn=10, restrict_vocab=None) is also available in the gensim package.

Find the top-N most similar words by vector.

Parameters:

• vector (numpy.array) – Vector from which similarities are to be computed.

• topn ({int, False}, optional) – Number of top-N similar words to return. If topn is False, similar_by_vector returns the vector of similarity scores.

• restrict_vocab (int, optional) – Optional integer which limits the range of vectors which are searched for most-similar values. For example, restrict_vocab=10000 would only check the first 10000 word vectors in the vocabulary order. (This may be meaningful if you’ve sorted the vocabulary by descending frequency.)

Returns: Sequence of (word, similarity).

Return type: list of (str, float)