我们首先将文本进行分句和分词处理。...我们可以使用NLTK库中的sent_tokenize和word_tokenize函数来完成这些操作。...示例代码如下:# 分句sentences = sent_tokenize(raw_data)# 分词tokenized_sentences = [word_tokenize(sentence.lower...我们可以使用NLTK库中提供的停用词列表进行去除。
下列哪项不是NLTK模块实现词条化方法的是( )A.sent_tokenize()B.word_tokenize()C.PunktWordTokenizer()D.tok
NLTK是Python的自然语言处理工具包，在NLP领域中，最常使用的一个Python库。 什么是NLP？ 简单来说，自...
vue是一款轻量级的mvvm框架，追随了面向对象思想，使得实际操作变得方便，但是如果使用不当，将会面临着到处...
"""sents = [word_tokenize(t)fortinsent_tokenize(doc)]fori,sentinenumerate(sents):ifqueryinsent: fullname = find_abr_fn(sent,query)iffullname !=-1:returnfullnameelse: j =1whilei-j >=0andj <= Num:iffind_abr_fn(sent[i-j],query) ==-1: ...
sent_tokenize(sentences)) <= 2): return sentences else: #we have enough sentences to do a readability overhaul wordDimensions = [] #this gives every word an assigned dimension in the vector for sent in nltk.sent_tokenize(sentences): for word in nltk.word_tokenize(sent): if word not in...
) <=2):returnsentenceselse:#we have enough sentences to do a readability overhaulwordDimensions = []#this gives every word an assigned dimension in the vectorforsentinnltk.sent_tokenize(sentences):forwordinnltk.word_tokenize(sent):ifwordnotinwordDimensions:#no duplicateswordDimensions.append(word...
text = {'text': args['text']}printtextprintsent_tokenize(text['text'])printword_tokenize(text['text'])returntext['text'] 开发者ID:lhofer,项目名称:Flask_text_processing_API,代码行数:7,代码来源:api_old.py 示例2: split_sentence_based_on_rules ...