python nltk -- sentences/phrases 的词干列表

Question

我的列表中有一堆句子，我想使用 nltk 库来阻止它。我可以一次提取一个句子，但是我在从列表中提取句子并将它们重新组合在一起时遇到了问题。我缺少一个步骤吗？ nltk 库很新。谢谢！

import nltk 
from nltk.stem import PorterStemmer 
ps = PorterStemmer()

# Success: one sentences at a time 
data = 'the gamers playing games'
words = word_tokenize(data)
for w in words:
    print(ps.stem(w))


# Fails: 

data_list = ['the gamers playing games',
            'higher scores',
            'sports']
words = word_tokenize(data_list)
for w in words:
    print(ps.stem(w))

# Error: TypeError: expected string or bytes-like object
# result should be: 
['the gamer play game',
 'higher score',
 'sport']

Answer 1

您正在将列表传递给 word_tokenize，但您不能。

解决方案是将您的逻辑包装在另一个 for-loop,

data_list = ['the gamers playing games','higher scores','sports']
for words in data_list:
    words = tokenize.word_tokenize(words)
    for w in words:
        print(ps.stem(w))

>>>>the
gamer
play
game
higher
score
sport

Answer 2

import nltk
from nltk.tokenize import sent_tokenize
from nltk.stem import PorterStemmer

sentence = """At eight o'clock on Thursday morning, Arthur didn't feel very good. So i take him to hospital."""

sentence = sentence.lower()

word_tokens = nltk.word_tokenize(sentence)
sent_tokens = sent_tokenize(sentence)

stemmer = PorterStemmer()
stemmed_word = []
stemmed_sent = []
for token in word_tokens:
    stemmed_word.append(stemmer.stem(token))
    
for sent_token in sent_tokens:
    stemmed_sent.append(stemmer.stem(sent_token))
    
print(stemmed_word)
print(stemmed_sent)

Answer 3

为了阻止并重新编译回列表数据结构，我会选择：

ps = PorterStemmer()
data_list_s = [] 
for words in data_list:
    words = word_tokenize(words)
    words_s = ''
    for w in words:
        w_s = ps.stem(w)
        words_s+=w_s+' '
    data_list_s.append(words_s)

这会将 data_list 中每个元素的词干结果放入一个名为 data_list_s 的新列表中。

python nltk -- sentences/phrases 的词干列表

python nltk -- stemming list of sentences/phrases

python

porter-stemmer

nltk

stem