title: Clustering method for FastText
body: <p>I am using pre-trained fastText (<a href="https://fasttext.cc/" rel="nofollow noreferrer">https://fasttext.cc/</a>) vectors to perform clustering on short chat messages. This means that the resulting vector will be an average of the tokens composing the message.</p>
  
  <p>I started using k-means initially but I am now wondering whether it is the right choice. For instance, K-means uses the Euclidean distance while in most cases, word embedding similarity is computed using cosine similarity.</p>
  
  <p>How to choose the right clustering method in this case?</p>