import jieba def get_stop_words(filepath) -> list: return open(filepath, 'r', encoding='utf-8').readlines()[0].split(',') # 对句子进行分词 def seg_sentence(sentence, stop_words): sentence_seged = jieba.cut(sentence.strip()) stopwords = stop_words # 这里加载停用词 outstr = ''...
以下是一个简单示例,演示如何使用nltk库的停词表去除文本中的停词: fromnltk.corpusimportstopwordsfromnltk.tokenizeimportword_tokenize stop_words=set(stopwords.words('english'))text="This is an example sentence demonstrating how to remove stopwords."tokens=word_tokenize(text)filtered_text=[wordforwordint...
return custom_stopwords_list 我们指定使用的停用词表,为我们已经下载保存好的哈工大停用词表文件。 stop_words_file = "stopwordsHIT.txt" stopwords = get_custom_stopwords(stop_words_file) 看看我们的停用词列表的后10项: stopwords[-10:] 这些大部分都是语气助词,作为停用词去除掉,不会影响到语句的实质含义。
(filepath, 'r').readlines()] return stopwords # 对句子进行分词 def seg_sentence(sentence): sentence_seged = jieba.cut(sentence.strip()) stopwords = stopwordslist('G:\\哈工大停用词表.txt') # 这里加载停用词的路径 outstr = '' for word in sentence_seged: if word not in stopwords: ...
stopwordslist=stopwordslist("stopwords_txt/total_stopwords_after_filter.txt")#review="刚刚才离开酒店,这是一次非常愉快满意住宿体验。酒店地理位置对游客来说相当好,离西湖不行不到十分钟,离地铁口就几百米,周围是繁华商业中心,吃饭非常方便。酒店外观虽然有些年头,但里面装修一点不过时,我是一个对卫生要求高的...
我正在使用numpy删除python中的停用词。停止词文件将作为列表导入。这就是我的想法:# loop through the stop words list, and remove each one fromstopwords: words.remove(line) 浏览0提问于2017-02-12得票数 1 2回答 使用OpenNLP从解析的内容中删除停用词 ...
stopwords = pd.read_csv('StopwordsCN.txt', encoding='utf8', names=['stopword'], index_col=False) stopwords.head() 接下里我们只要适当更改分词的代码即可在分词的时候去掉停用词: # 转化词列表 stop_list = stopwords['stopword'].tolist() # 去除停用...
stopwords = stopwordslist('filename') # 这里加载停用词的路径 outstr = '' for word in sentence_seged: if word not in stopwords: if word != '\t': outstr += word outstr += " " return outstr inputs = open('filename', 'r') #加载要处理的文件的路径 ...
#引入停用词表defstopwordslist(filepath): stopwords= [line.strip()forlineinopen(filepath,'r', encoding='utf-8').readlines()]returnstopwords 再进行jieba分词,去停使用的是哈工大停用词表 #用lcut使得分词后为一个lists_list =jieba.lcut(content_str) ...
stopwords = [line.strip() for line in open(filepath, 'r', encoding='utf-8').readlines()] return stopwords 对句子进行分词 stopwords = stopwordslist('D:\2019年python代码\python_book\chapter4\stopwords.txt') # 这里加载停用词的路径