title: How to find the most meaningful words in the text with using word2vec?
body: <p>So, for instance, I'm typing, as an input, some sentence with some semantic meaning and, as an output, I get some list of closest (in cosine distance) words (mostly single words).</p>
  
  <p>But I want to understand which cluster my sentence belongs to and compute how far is located each word from it. And eliminate non-meaningful words from sentence.</p>
  
  <p>For example:</p>
  
  <p>"I want to buy a pizza";</p>
  
  <p>"pizza": 0.99123</p>
  
  <p>"buy": 0.7834</p>
  
  <p>"want": 0.1443</p>
  
  <p>How such requirement can be achieved out of the box, without any C coding? </p>
  
  <p>Maybe I need to compute cosine distance equation for this? </p>
  
  <p>Thank you!</p>