def rank_article(self, article_as_dict):
article_vendor = self.get_vendor(article_as_dict)
if article_vendor is None:
logger.error("No vendor for '%s'" % article_as_dict['news_vendor'])
return
stored_article = self.save_article(article_vendor, article_as_dict)
if stored_article is None:
logger.error("Could not save article")
return
#get users for vendor
users = User.objects(subscriptions=article_vendor)
#rank article for each user to her profile
for u in users:
user_model = UserModelCentroid(user_id=u.id, extractor=self.feature_extractor_)
ranking = user_model.rank(stored_article)
self.save_rating(u, stored_article, ranking)
logger.info("Store rating for user: " + str(ranking))
def setUp(self):
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.DEBUG)
config = load_config(file_path="/vagrant/config.yaml", logger=logger, exit_with_error=True)
#Connect to test database
connect("nyan_test", port=27017)
fill_database()
#connect(config['database']['db-name'],
# username= config['database']['user'],
# password= config['database']['passwd'],
# port = config['database']['port'])
self.user_id = User.objects(email=u'*****@*****.**').first().id
#self.feature_extractor = EsaFeatureExtractor(prefix = config['prefix'])
self.feature_extractor = TfidfFeatureExtractor(prefix=config['prefix'])
self.trainer = UserModelCentroid(self.user_id, extractor=self.feature_extractor)
class UserModelCentroidTest(unittest.TestCase):
def setUp(self):
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.DEBUG)
config = load_config(file_path="/vagrant/config.yaml", logger=logger, exit_with_error=True)
#Connect to test database
connect("nyan_test", port=27017)
fill_database()
#connect(config['database']['db-name'],
# username= config['database']['user'],
# password= config['database']['passwd'],
# port = config['database']['port'])
self.user_id = User.objects(email=u'*****@*****.**').first().id
#self.feature_extractor = EsaFeatureExtractor(prefix = config['prefix'])
self.feature_extractor = TfidfFeatureExtractor(prefix=config['prefix'])
self.trainer = UserModelCentroid(self.user_id, extractor=self.feature_extractor)
def tearDown(self):
clear_database()
@unittest.skip("not for now")
def test_train(self):
self.trainer.train()
self.assertAlmostEqual(self.trainer.learned_user_model.data[0][1],
0.1553, 4)
@unittest.skip("no saving yet")
def test_save(self):
self.trainer.train()
self.trainer.save()
user_model = UserModel.objects(user_id=self.user_id).first()
self.assertAlmostEqual(user_model.data[0][1],
0.0021, 4)
logging.basicConfig(format="%(asctime)s : %(levelname)s : %(message)s", level=logging.DEBUG, filename=options.log)
# load config
logger = logging.getLogger("main")
logging.info("Load config")
config_ = load_config(options.config, logger, exit_with_error=True)
if config_ is None:
logger.error("No config. Exit.")
sys.exit(1)
# Connect to mongo database
connect(
config_["database"]["db-name"],
username=config_["database"]["user"],
password=config_["database"]["passwd"],
port=config_["database"]["port"],
)
feature_extractor = TfidfFeatureExtractor(prefix=config_["prefix"])
logger.info("Learn user model...")
users = User.objects()
for u in users:
logger.info("for %s" % u.name)
trainer = UserModelCentroid(user_id=u.id, extractor=feature_extractor)
trainer.train()
trainer.save()
logger.info("...done.")
