The last step is to actually carry out classification or clustering using the feature engineered matrix or word vectors. We could use any classification algorithm and feed the feature vector to carry out classification or clustering.

Similar to carrying out the clustering, different similarity measures could be used, such as Cosine Distance or Levenshtein distance.