def load(self, records):
self.records = records
self.ratings_matrix = basic_knn.create_ratings_matrix(records)
self.reviews_matrix = create_reviews_matrix(records)
self.user_dictionary = extractor.initialize_users(self.records, False)
self.user_ids = extractor.get_groupby_list(self.records, 'user_id')
# self.lda_model =\
# lda_context_utils.discover_topics(text_reviews, self.num_topics)
if self.reviews:
lda_based_context = LdaBasedContext()
lda_based_context.reviews = self.reviews
lda_based_context.init_reviews()
else:
text_reviews = []
for record in self.records:
text_reviews.append(record['text'])
lda_based_context = LdaBasedContext(text_reviews)
lda_based_context.init_reviews()
self.context_rich_topics = lda_based_context.get_context_rich_topics()
self.lda_model = lda_based_context.topic_model
print('building similarity matrix', time.strftime("%H:%M:%S"))
self.context_matrix = self.create_context_matrix(records)
self.similarity_matrix = self.create_similarity_matrix()
print('finished building similarity matrix', time.strftime("%H:%M:%S"))
def load_context(self, records):
if self.reviews:
lda_based_context = LdaBasedContext()
lda_based_context.reviews = self.reviews
lda_based_context.init_reviews()
else:
text_reviews = []
for record in records:
text_reviews.append(record['text'])
lda_based_context = LdaBasedContext(text_reviews)
lda_based_context.init_reviews()
self.context_rich_topics = lda_based_context.get_context_rich_topics()
self.lda_model = lda_based_context.topic_model
for user in self.user_dictionary.values():
user.item_contexts = lda_context_utils.get_user_item_contexts(
records, self.lda_model, user.user_id, True
)
