title: How can i cluster document using k-means (Flann with python)?
body: <p>I want to cluster documents based on similarity.</p>
  
  <p>I haved tried ssdeep (similarity hashing), very fast but i was told that k-means is faster and flann is fastest of all implementations, and more accurate so i am trying flann with python bindings but i can't find any example how to do it on text (it only support array of numbers).</p>
  
  <p>I am very very new to this field (k-means, natural language processing). What i need is speed and accuracy.</p>
  
  <p>My questions are: </p>
  
  <ol>
  <li>Can we do document similarity grouping / Clustering using KMeans (Flann do not allow any text input it seems )</li>
  <li>Is Flann the right choice? If not please suggest me High performance library that support text/docs clustering, that have python wrapper/API.</li>
  <li>Is k-means the right algorithm?</li>
  </ol>