在python中是否有一些考虑到重音的编辑距离。 例如,举行以下财产
d('ab', 'ac') > d('àb', 'ab') > 0
答案 0 :(得分:5)
In [1]: import unicodedata, string
In [2]: from Levenshtein import distance
In [3]: def remove_accents(data):
...: return ''.join(x for x in unicodedata.normalize('NFKD', data)
...: if x in string.ascii_letters).lower()
In [4]: def norm_dist(s1, s2):
...: norm1, norm2 = remove_accents(s1), remove_accents(s2)
...: d1, d2 = distance(s1, s2), distance(norm1, norm2)
...: return (d1+d2)/2.
In [5]: norm_dist(u'ab', u'ac')
Out[5]: 1.0
In [6]: norm_dist(u'àb', u'ab')
Out[6]: 0.5
答案 1 :(得分:2)
Unicode允许将重音字符分解为基本字符加上组合重音字符;例如à
分解为a
,然后是严重重音组合。
您希望使用规范化形式NFKD转换这两个字符串,NFKD会分解重音字符并将兼容性字符转换为规范形式,然后使用编辑距离度量标准对插入和删除之上的替换进行排名。
答案 2 :(得分:1)
以下是基于difflib和unicodedata的解决方案,没有任何依赖关系:
import unicodedata
from difflib import Differ
# function taken from https://stackoverflow.com/a/517974/1222951
def remove_accents(input_str):
nfkd_form = unicodedata.normalize('NFKD', input_str)
only_ascii = nfkd_form.encode('ASCII', 'ignore').decode()
return only_ascii
def compare(wrong, right):
# normalize both strings to make sure equivalent (but
# different) unicode characters are canonicalized
wrong = unicodedata.normalize('NFKC', wrong)
right = unicodedata.normalize('NFKC', right)
num_diffs = 0
index = 0
differences = list(Differ().compare(wrong, right))
while True:
try:
diff = differences[index]
except IndexError:
break
# diff is a string like "+ a" (meaning the character "a" was inserted)
# extract the operation and the character
op = diff[0]
char = diff[-1]
# if the character isn't equal in both
# strings, increase the difference counter
if op != ' ':
num_diffs += 1
# if a character is wrong, there will be two operations: one
# "+" and one "-" operation
# we want to count this as a single mistake, not as two mistakes
if op in '+-':
try:
next_diff = differences[index+1]
except IndexError:
pass
else:
next_op = next_diff[0]
if next_op in '+-' and next_op != op:
# skip the next operation, we don't want to count
# it as another mistake
index += 1
# we know that the character is wrong, but
# how wrong is it?
# if the only difference is the accent, it's
# a minor mistake
next_char = next_diff[-1]
if remove_accents(char) == remove_accents(next_char):
num_diffs -= 0.5
index += 1
# output the difference as a ratio of
# (# of wrong characters) / (length of longest input string)
return num_diffs / max(len(wrong), len(right))
试验:
for w, r in (('ab','ac'),
('àb','ab'),
('être','etre'),
('très','trés'),
):
print('"{}" and "{}": {}% difference'.format(w, r, compare(w, r)*100))
"ab" and "ac": 50.0% difference
"àb" and "ab": 25.0% difference
"être" and "etre": 12.5% difference
"très" and "trés": 12.5% difference