def start(self):
# DatabaseQueries.createTables()
self.modelStore = ModelStore() # "database" of models
self.userAnalyzer = UserAnalyzer(
) # classify user type: anonymous? registered new? or registered old?
self.trainingCenter = TrainingCenter(self.modelStore)
self.ranker = Ranker() # just rank the recommended items
# once start should firstly train the models and immediately have recommendations on home page
self.trainingCenter.trainModel(
) # NOTE: need to firstly train models once for a welcome page
self.recEngine = RecEngine(self.userAnalyzer, self.modelStore,
DatabaseQueries.getNumRatingsPerUser())
def start(self):
# each object here simulates the API calls through network
# passing an object A to the constructor of B means A will communication to B
self.db.startEngine()
self.ranker = Ranker(self.numberToServe, self.db)
self.user_analyzer = UserAnalyzer()
self.model_store = ModelStore()
self.online_learner = OnlineLearner(self.db, self.model_store)
self.offline_learner = OfflineLearner(self.db, self.model_store)
self.increment()
self.rec_engine = RecEngine(
self.user_analyzer, self.model_store,
self.db.connTable[DatabaseInterface.USER_ACTIVITY_KEY])
def start(self):
self.db.startEngine()
self.ranker = Ranker(self.numberToServe, self.db)
self.userAnalyzer = UserAnalyzer()
self.modelStore = ModelStore()
self.offlineLearner = OfflineLearner(self.db, self.modelStore)
self.onlineLearner = OnlineLearner(self.db, self.modelStore)
#so that immediately after we start, we can start to give recommendations
self.offlineLearner.trainModel()
#had to extract it here
self.recEngine = RecEngine(
self.userAnalyzer, self.modelStore,
self.db.extract(DatabaseInterface.USER_ACTIVITY_KEY))
def start(self):
# each object here simulates the API calls through network
# passing an object A to the constructor of B means A will communication to B
self.db.startEngine()
self.ranker = Ranker(self.numberToServe, self.db)
self.userAnalyzer = UserAnalyzer()
self.modelStore = ModelStore()
self.offlineLearner = OfflineLearner(self.db, self.modelStore)
self.onlineLearner = OnlineLearner(self.db, self.modelStore)
self.offlineLearner.trainModel()
# when we start the webserver, let offline learner to train the models,
# so that after the start(), we can start to give recommendation
self.recEngine = RecEngine(
self.userAnalyzer, self.modelStore,
self.db.extract(DatabaseInterface.USER_ACTIVITY_KEY))