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Sergey Elpashev
2025-01-06 22:24:51 +03:00
parent 22ba0c97c5
commit fa05f39b24
6 changed files with 238 additions and 13 deletions
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10
anixarttierlist/group.py
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@@ -5,7 +5,7 @@ from sklearn.feature_extraction.text import CountVectorizer
from sklearn.metrics.pairwise import cosine_similarity
def find_first_substring(strings: List[str]):
def find_first_substring(strings: List[str]) -> str:
if not strings:
return ""
if len(strings) == 1:
@@ -20,12 +20,12 @@ def find_first_substring(strings: List[str]):
return ""
def group_by_common_part(strings, n=3):
def group_by_common_part(strings, n=3) -> List[str]:
vectorizer = CountVectorizer(analyzer='char_wb', ngram_range=(n, n))
X = vectorizer.fit_transform(strings)
similarity_matrix = cosine_similarity(X)
similarity_treshold = .5
similarity_threshold = .5
groups = []
assigned = [False] * len(strings)
@@ -38,12 +38,12 @@ def group_by_common_part(strings, n=3):
assigned[i] = True
for j in range(i+1, len(strings)):
if assigned[j] or similarity_matrix[i, j] < similarity_treshold:
if assigned[j] or similarity_matrix[i, j] < similarity_threshold:
continue
group.append(strings[j])
assigned[j] = True
common_part = find_first_substring(group)
groups.append(common_part)
groups.append((group, common_part))
return groups