def update_with_sentences(self, parsed_user):
    # Check user input for names, focus appropriately
    for word in parsed_user.split(' '):
      base, pos = parse_utils.split_parsed(word)
      if (pos == 'NNP'):
        self.focus_on(base)

    self.step()
Ejemplo n.º 2
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  def update_with_sentences(self, parsed_combined):
    char_count = 0;
    last_state_update = 0
    for word in parsed_combined.split(' '):
      char_count += len(word)
      base, pos = parse_utils.split_parsed(word)

      if (pos == 'JJ'):
        base = base.lower()
        if base in adjective_to_vector_map:
          last_state_update = char_count
          new_topic_vector = adjective_to_vector_map[base]
          # Combine vectors in EWMA like way
          self.topic = [self.topic_old_weight * old * 0.5 ** ((char_count - last_state_update) / self.topic_half_life) \
            + new * (1 - self.topic_old_weight) for old, new in zip(self.topic, new_topic_vector)]

    # Decay for all remaining characters
    self.topic = [x * 0.5 ** ((char_count - last_state_update) / self.topic_half_life) for x in self.topic]