本文整理匯總了Python中nltk.WordNetLemmatizer.stem方法的典型用法代碼示例。如果您正苦於以下問題：Python WordNetLemmatizer.stem方法的具體用法？Python WordNetLemmatizer.stem怎麽用？Python WordNetLemmatizer.stem使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類nltk.WordNetLemmatizer的用法示例。
在下文中一共展示了WordNetLemmatizer.stem方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: text2sents
# 需要導入模塊: from nltk import WordNetLemmatizer [as 別名]
# 或者: from nltk.WordNetLemmatizer import stem [as 別名]
def text2sents(text, lemmatize=False, stemmer=None):
"""
converts a text into a list of sentences consisted of normalized words
:param text: list of string to process
:param lemmatize: if true, words will be lemmatized, otherwise -- stemmed
:param stemmer: stemmer to be used, if None, PortedStemmer is used. Only applyed if lemmatize==False
:return: list of lists of words
"""
sents = sent_tokenize(text)
tokenizer = RegexpTokenizer(r'\w+')
if lemmatize:
normalizer = WordNetLemmatizer()
tagger = PerceptronTagger()
elif stemmer is None:
normalizer = PorterStemmer()
else:
normalizer = stemmer
sents_normalized = []
for sent in sents:
sent_tokenized = tokenizer.tokenize(sent)
if lemmatize:
sent_tagged = tagger.tag(sent_tokenized)
sent_normalized = [normalizer.lemmatize(w[0], get_wordnet_pos(w[1])) for w in sent_tagged]
else:
sent_normalized = [normalizer.stem(w) for w in sent_tokenized]
sents_normalized.append(sent_normalized)
return sents_normalized