class_docstr: This implements wrapper for gensim lsa and tfidf analysis of text collection
code: def text_similarity(self, t1, t2):
      if self._model == "tfidf":
          t1_vec = matutils.any2sparse(self.text2model(t1))
          t2_vec = matutils.any2sparse(self.text2model(t2))
          return matutils.cossim(t1_vec, t2_vec)
      else:
          t1_vec = matutils.any2sparse(self.text2model(t1))
          t2_vec = matutils.any2sparse(self.text2model(t2))
          return matutils.cossim(t1_vec, t2_vec)
  
file_path: sematch/sematch/semantic/analysis.py
imports: from gensim import corpora, models, similarities, matutils
label_desc: Use image node_id 3 for calling the TextAnalysis obj's underlying member method code with example usage: obj.text_similarity(t1, t2) and returns: matutils, matutils