code: def _weight_concepts(self, tokens, term_concept_map):
          
  
          weights = {c: 0 for c in term_concept_map.values()}
          for t in tokens:
              # Skip terms that aren't one of the PoS we used
              if t not in term_concept_map:
                  continue
              con = term_concept_map[t]
              weights[con] += 1
  
          # TO DO paper doesn't mention normalizing these weights...should we?
          return weights
docs: Calculates weights for concepts in a document.
  
          This is just the frequency of terms which map to a concept.