def extract_results(labels, original_data, review_bodys):
# print number of elements in each cluster
cluster_counts = Counter(labels)
print(cluster_counts)
clusters = {}
pattern_matcher = PatternMatcher()
# find and print dbscan result on actual text data - review_bodys
for i in set(labels):
if i != -1: # do not print if noise (-1)
clusters[i] = []
print(i, "----")
for x in range(len(review_bodys)):
if labels[x] == i:
print(">>>", (review_bodys[x]))
sentence = get_review(review_bodys[x])
matches = pattern_matcher.find_matches(sentence)
clusters[i].append((review_bodys[x][0], sentence, matches))
print(clusters[i], "\n")
print(clusters)
input()
return pattern_matcher.extract_objects(clusters)
