对于文本分词,此处使用的是python自带的jieba包进行,首先我们要先读取我们所需要分词的文章,然后使用jieba.cut进行分词,注意分词时要将这些段落归并成同一个字符串,然后输出的是一个列表。最后写入一个文件中
import jieba.analyse
test1 =""
fencilist=[]
with open(r"testtxt",'r',encoding="UTF-8") as test:
for line in test:
line.strip()
test1+=line
fencilist=jieba.cut(test1)
fencilist=list(set(fencilist))
with open(r"fenciescult",'w',encoding="UTF-8") as f:
for i in fencilist:
f.write(i+'\n')
在去除停用词时,我们可以将停用词进行提取,并存放在一个列表中,然后将分好的词存放在一个列表中,用for循环进行一个一个判断是否在停用词库中,如果不在,就存放在一个新的列表中,得到最终结果。
stopwordlist=[]
fencilist=[]
resultlist=[]
with open(r"stopwords",'r',encoding="UTF-8") as f:
for i in f:
stopwordlist.append(i)
with open(r"fenciescult",'r',encoding="UTF-8") as test:
for line in test:
fencilist.append(line.strip())
for i in fencilist:
if(i not in stopwordlist):
resultlist.append(i)
with open(r"result",'w',encoding="UTF-8") as xx:
for x in resultlist:
xx.write(x+'\n')
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