class_docstr: This class contains TF-IDF model and LSA model of text-text similarity.
class_docstr_tok: ["This","class","contains","TF-IDF","model","and","LSA","model","of","text-text","similarity","."]
code: def word_tokenize(self, text):
      tokens = self._tokenizer.tokenize(text.lower())
      tokens = [t for t in tokens if len(t) > 2]
      tokens = [w.lower() for w in tokens]
      tokens = [w for w in tokens if w not in self._stopwords]
      return tokens
  
imports: from numpy import array
  from gensim import matutils
label_desc: Use image node_id 2 for calling the TextRelatedness obj's underlying member method code with example usage: obj.word_tokenize(text) and returns: tokens