how to find similar words for a certain word in tensorflow_word2vec like using model.most_similar in gensim?

Question

I've using tensorflow to build word2vec model,reference here：https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/word2vec/word2vec_basic.py#L118

my question is that, how can i find top n similar words for a certain word.I know in gensim, I can save and load word2vec model,and then use model.most_similar to find what I want.but how in tensorflow and even more is there any way to save model in tensorflow since i find what i get is only an embedding vector,is that right?

Answer 1

I think as long as you have computed the weight vector for each token, then you can manipulate all the tokens in the vector space. You can simply calculate the cosine similarity between each vector and then sort by score. For your reference, you can look at the source code of most_similar method implemented in gensim word2vec model. Hope this helps.