def calculate_similar_score_keywords(mentees, mentors):
mentor_keywords = get_keyword_list(mentors)
mentee_keywords = get_keyword_list(mentees)
glove = Glove(mentor_keywords + mentee_keywords)
scores = []
for mentee_keyword, mentee in zip(mentee_keywords, mentees):
glove_result = glove.get_score(mentee_keyword)
scores.append(glove_result)
return scores
def calculate_similar_score_flipped(mentees, mentors):
mentor_keywords = get_keyword_list(mentors)
mentee_contents = [mentee.content for mentee in mentees]
glove = Glove(mentee_contents)
scores = []
for mentee_keyword, mentee in zip(mentor_keywords, mentees):
glove_result = glove.get_score(mentee_keyword)
scores.append(glove_result)
return scores
def reward_similarity_keyword_multiple_keywords_glove(matrix,
mentees,
mentors,
score=0,
**kwargs):
mentor_keywords = get_keyword_list(mentors)
mentee_keywords = get_keyword_list(mentees)
all_mentee_keywords = []
for i, mentor in enumerate(mentors):
for j, mentee in enumerate(mentees):
all_mentee_keywords.append(str(mentee_keywords))
glove_result = glove_score_1v1(mentor_keywords, all_mentee_keywords)
average = sum(glove_result) / len(glove_result)
# Take result from glove and act accordingly
for j, mentee in enumerate(mentees):
if glove_result[j] > average:
matrix[i][j] += score
return matrix
def reward_similarity_keywords_to_texts_new(matrix,
mentees,
mentors,
score=0,
**kwargs):
result_matrix = get_or_calculate_cache("glove_cache_new_{}.json".format(
global_vars.ROUND),
calculate_similar_score_new,
mentees=mentees,
mentors=mentors)
first = True
mentee_keywords = get_keyword_list(mentees)
for mentee_idx, (mentee_scores,
keyword) in enumerate(zip(result_matrix,
mentee_keywords)):
if first:
first = False
continue
if keyword == ['nan']:
continue
# print(keyword)
if isinstance(mentee_scores, float):
continue
try:
top_5 = sorted(range(len(mentee_scores)),
key=lambda i: mentee_scores[i])[-6:]
except TypeError as e:
print("Something went wrong")
continue
for index in top_5:
if index > len(mentors):
continue
matrix[index][mentee_idx] += score
return matrix