How to use word2vec to calculate the similarity distance by giving 2 words?

Question

Word2vec is a open source tool to calculate the words distance provided by Google. It can be used by inputting a word and output the ranked word lists according to the similarity. E.g. Input: ``` france ``` Output: ``` Word Cosine distance spain 0.678515 belgium 0.665923 netherlands 0.652428 italy 0.633130 switzerland 0.622323 luxembourg 0.610033 portugal 0.577154 russia 0.571507 germany 0.563291 catalonia 0.534176 ``` However, what I need to do is to calculate the similarity distance by giving 2 words. If I give the 'france' and 'spain', how can I get the score 0.678515 without reading the whole words list by giving just 'france'.

Accepted Answer

gensim has a Python implementation of Word2Vec which provides an in-built utility for finding similarity between two words given as input by the user. You can refer to the following:

- Intro: http://radimrehurek.com/gensim/models/word2vec.html

- Tutorial: http://radimrehurek.com/2014/02/word2vec-tutorial/

UPDATED: Gensim 4.0.0 and above

The syntax in Python for finding similarity between two words goes like this:

```
>> from gensim.models import Word2Vec
>> model = Word2Vec.load(path/to/your/model)
>> model.wv.similarity('france', 'spain')
```

How to use word2vec to calculate the similarity distance by giving 2 words?

Solution

Problem