code: def _compute_tf(self, sentences):
          
          content_words = self._get_all_content_words_in_doc(sentences)
          content_words_count = len(content_words)
          content_words_freq = self._compute_word_freq(content_words)
          content_word_tf = dict((k, v / content_words_count) for (k, v) in content_words_freq.items())
          return content_word_tf
docs: Computes the normalized term frequency as explained in http://www.tfidf.com/