SYMBOL INDEX (28 symbols across 6 files)

FILE: 基于CNN的电影推荐系统/model_code/data_download.py
  function download_data (line 15) | def download_data():
  function extract_data (line 30) | def extract_data():
  function unzip (line 42) | def unzip(data_name, from_path, to_path):
  class DLProgress (line 49) | class DLProgress(tqdm):
    method hook (line 54) | def hook(self, block_num=1, block_size=1, total_size=None):

FILE: 基于CNN的电影推荐系统/model_code/data_processing.py
  function user_data_processing (line 13) | def user_data_processing():
  function movie_data_processing (line 35) | def movie_data_processing(title_length = 16):
  function rating_data_processing (line 92) | def rating_data_processing():
  function get_feature (line 103) | def get_feature():

FILE: 基于CNN的电影推荐系统/model_code/movie_nn.py
  function get_inputs (line 38) | def get_inputs():
  function get_movie_id_embed_layer (line 50) | def get_movie_id_embed_layer(movie_id):
  function get_movie_categories_embed_layer (line 62) | def get_movie_categories_embed_layer(movie_categories, combiner = 'sum'):
  function get_movie_cnn_layer (line 80) | def get_movie_cnn_layer(movie_titles, dropout_keep_prob, window_sizes = ...
  function get_movie_feature_layer (line 122) | def get_movie_feature_layer(

FILE: 基于CNN的电影推荐系统/model_code/recommendation.py
  function get_tensors (line 23) | def get_tensors(loaded_graph):
  function rating_movie (line 42) | def rating_movie(user_id, movie_id_val):
  function save_movie_feature_matrix (line 71) | def save_movie_feature_matrix():
  function save_user_feature_matrix (line 105) | def save_user_feature_matrix():
  function load_feature_matrix (line 130) | def load_feature_matrix(path):
  function recommend_same_type_movie (line 145) | def recommend_same_type_movie(movie_id, top_k=5):
  function recommend_your_favorite_movie (line 178) | def recommend_your_favorite_movie(user_id, top_k=5):
  function recommend_other_favorite_movie (line 208) | def recommend_other_favorite_movie(movie_id, top_k=5):

FILE: 基于CNN的电影推荐系统/model_code/training.py
  function get_targets (line 39) | def get_targets():
  function get_batches (line 44) | def get_batches(Xs, ys, batch_size):

FILE: 基于CNN的电影推荐系统/model_code/user_nn.py
  function get_inputs (line 34) | def get_inputs():
  function get_user_embedding (line 45) | def get_user_embedding(uid, user_gender, user_age, user_job):
  function get_user_feature_layer (line 71) | def get_user_feature_layer(
  function user_feature (line 99) | def user_feature():