| from .SimilarityScorev2 import similarity_score |
| import numpy as np |
|
|
| def find_similar_entities(list1, list2): |
| similar_strings = [] |
| list1_copy = list1.copy() |
| for string in list1: |
| if string in list2: |
| similar_strings.append(string) |
| list1_copy.remove(string) |
| list2.remove(string) |
| return similar_strings, list1_copy, list2 |
|
|
| def sim_metric(ref, gen): |
| if len(ref)==0 or len(gen)==0: |
| return 0 |
| else: |
| similar, ref_remain, gen_remain = find_similar_entities(ref, gen) |
| sim_score = similarity_score(ref,gen) |
|
|
| return (len(similar)+np.sum(sim_score))/(len(similar)+len(sim_score)) |
