我有一组串联的词，我想将它们分成数组
例如 :
split_word("acquirecustomerdata")
=> ['acquire', 'customer', 'data']
我找到了
pyenchant，但不适用于64位Windows。然后，我尝试将每个字符串拆分为子字符串，然后将它们与wordnet进行比较以找到等效的单词。
例如 :
from nltk import wordnet as wn
def split_word(self, word):
result = list()
while(len(word) > 2):
i = 1
found = True
while(found):
i = i + 1
synsets = wn.synsets(word[:i])
for s in synsets:
if edit_distance(s.name().split('.')[0], word[:i]) == 0:
found = False
break;
result.append(word[:i])
word = word[i:]
print(result)
但是这种解决方案不确定，而且时间太长。
因此，我正在寻找您的帮助。
谢谢
最佳答案
在Word Segmentation Task的工作中检查-Norvig。
from __future__ import division
from collections import Counter
import re, nltk
WORDS = nltk.corpus.brown.words()
COUNTS = Counter(WORDS)
def pdist(counter):
"Make a probability distribution, given evidence from a Counter."
N = sum(counter.values())
return lambda x: counter[x]/N
P = pdist(COUNTS)
def Pwords(words):
"Probability of words, assuming each word is independent of others."
return product(P(w) for w in words)
def product(nums):
"Multiply the numbers together. (Like `sum`, but with multiplication.)"
result = 1
for x in nums:
result *= x
return result
def splits(text, start=0, L=20):
"Return a list of all (first, rest) pairs; start <= len(first) <= L."
return [(text[:i], text[i:])
for i in range(start, min(len(text), L)+1)]
def segment(text):
"Return a list of words that is the most probable segmentation of text."
if not text:
return []
else:
candidates = ([first] + segment(rest)
for (first, rest) in splits(text, 1))
return max(candidates, key=Pwords)
print segment('acquirecustomerdata')
#['acquire', 'customer', 'data']
为了获得更好的解决方案，您可以使用bigram/trigram。
有关更多示例，请访问:Word Segmentation Task
关于python - 在python中拆分句子而没有空格(nltk？)，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/38125281/