def recommend(self, userID): lista = {} recommendations = self.movie_lens_recommender.predict_ratings(userID) # print len(recommendations) recommendations1 = dbt_rec(self.movie_lens_recommender.get_rated_movies(userID)) for recommendation in recommendations: if recommendation[0] in recommendations1: lista[recommendation[0]] = self.alpha * recommendation[1] + (1 - self.alpha) * recommendations1[recommendation[0]] del recommendations1[recommendation[0]] else: lista[recommendation[0]] = self.alpha * recommendation[1] for recommendation in recommendations1.keys(): lista[recommendation] = (1 - self.alpha) * recommendations1[recommendation] return lista
def recommend(self, userID): lista = {} recommendations = self.movie_lens_recommender.predict_ratings(userID) watched = self.movie_lens_recommender.get_rated_movies(userID) for elem in watched: print elem print "" recommendations1 = dbt_rec(watched, 500) for recommendation in recommendations: if recommendation[0] in recommendations1: lista[recommendation[0]] = self.alpha * recommendation[1] + (1 - self.alpha) * recommendations1[recommendation[0]] del recommendations1[recommendation[0]] else: lista[recommendation[0]] = self.alpha * recommendation[1] for recommendation in recommendations1.keys(): lista[recommendation] = (1 - self.alpha) * recommendations1[recommendation] return sorted(lista.iteritems(), key=operator.itemgetter(1), reverse=True)
def recommend(self, userID): lista = {} recommendations = self.movie_lens_recommender.predict_ratings(userID) # print len(recommendations) recommendations1 = dbt_rec( self.movie_lens_recommender.get_rated_movies(userID)) for recommendation in recommendations: if recommendation[0] in recommendations1: lista[recommendation[0]] = self.alpha * recommendation[1] + ( 1 - self.alpha) * recommendations1[recommendation[0]] del recommendations1[recommendation[0]] else: lista[recommendation[0]] = self.alpha * recommendation[1] for recommendation in recommendations1.keys(): lista[recommendation] = ( 1 - self.alpha) * recommendations1[recommendation] return lista
def recommend(self, userID): lista = {} recommendations = self.movie_lens_recommender.predict_ratings(userID) watched = self.movie_lens_recommender.get_rated_movies(userID) for elem in watched: print elem print "" recommendations1 = dbt_rec(watched, 500) for recommendation in recommendations: if recommendation[0] in recommendations1: lista[recommendation[0]] = self.alpha * recommendation[1] + ( 1 - self.alpha) * recommendations1[recommendation[0]] del recommendations1[recommendation[0]] else: lista[recommendation[0]] = self.alpha * recommendation[1] for recommendation in recommendations1.keys(): lista[recommendation] = ( 1 - self.alpha) * recommendations1[recommendation] return sorted(lista.iteritems(), key=operator.itemgetter(1), reverse=True)