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代碼封裝類：

#!/usr/bin/env python

# -*- coding:utf-8 -*-

import jieba

import os

import re

import time

from jpype import *

'''

title：利用結巴分詞進行文本語料的批量處理

1 首先對文本進行遍歷查找

2 創建原始文本的保存結構

3 對原文本進行結巴分詞和停用詞處理

4 對預處理結果進行標準化格式，并保存原文件結構路徑

author：白寧超

myblog：http://www.cnblogs.com/baiboy/

time：2017年4月28日10:03:09

'''

'''

創建文件目錄

path:根目錄下創建子目錄

'''

def mkdir(path):

# 判斷路徑是否存在

isExists=os.path.exists(path)

# 判斷結果

if not isExists:

os.makedirs(path)

print(path+' 創建成功')

return True

else:

pass

print('-->請稍后，文本正在預處理中...')

'''

結巴分詞工具進行中文分詞處理：

read_folder_path：待處理的原始語料根路徑

write_folder_path 中文分詞經數據清洗后的語料

'''

def CHSegment(read_folder_path,write_folder_path):

stopwords ={}.fromkeys([line.strip() for line in open('../Database/stopwords/CH_stopWords.txt','r',encoding='utf-8')]) # 停用詞表

# 獲取待處理根目錄下的所有類別

folder_list = os.listdir(read_folder_path)

# 類間循環

# print(folder_list)

for folder in folder_list:

#某類下的路徑

new_folder_path = os.path.join(read_folder_path, folder)

# 創建一致的保存文件路徑

mkdir(write_folder_path+folder)

#某類下的保存路徑

save_folder_path = os.path.join(write_folder_path, folder)

#某類下的全部文件集

# 類內循環

files = os.listdir(new_folder_path)

j = 1

for file in files:

if j > len(files):

break

# 讀取原始語料

raw = open(os.path.join(new_folder_path, file),'r',encoding='utf-8').read()

# 只保留漢字

# raw1 = re.sub("[A-Za-z0-9\[\`\~\!\@\#\$\^\&\*\(\)\=\|\{\}\'\:\;\'\,\[\]\.\\/\?\~\！\@\#\\\&\*\%]", "", raw)

# jieba分詞

wordslist = jieba.cut(raw, cut_all=False) # 精確模式

# 停用詞處理

cutwordlist=''

for word in wordslist:

if word not in stopwords and word=="\n":

cutwordlist+="\n" # 保持原有文本換行格式

elif len(word)>1 :

cutwordlist+=word+"/" #去除空格

#保存清洗后的數據

with open(os.path.join(save_folder_path,file),'w',encoding='utf-8') as f:

f.write(cutwordlist)

j += 1

'''

結巴分詞工具進行中文分詞處理：

read_folder_path：待處理的原始語料根路徑

write_folder_path 中文分詞經數據清洗后的語料

'''

def HanLPSeg(read_folder_path,write_folder_path):

startJVM(getDefaultJVMPath(), "-Djava.class.path=C:\hanlp\hanlp-1.3.2.jar;C:\hanlp", "-Xms1g", "-Xmx1g") # 啟動JVM，Linux需替換分號;為冒號:

stopwords ={}.fromkeys([line.strip() for line in open('../Database/stopwords/CH_stopWords.txt','r',encoding='utf-8')]) # 停用詞表

# 獲取待處理根目錄下的所有類別

folder_list = os.listdir(read_folder_path)

# 類間循環

# print(folder_list)

for folder in folder_list:

#某類下的路徑

new_folder_path = os.path.join(read_folder_path, folder)

# 創建一致的保存文件路徑

mkdir(write_folder_path+folder)

#某類下的保存路徑

save_folder_path = os.path.join(write_folder_path, folder)

#某類下的全部文件集

# 類內循環

files = os.listdir(new_folder_path)

j = 1

for file in files:

if j > len(files):

break

# 讀取原始語料

raw = open(os.path.join(new_folder_path, file),'r',encoding='utf-8').read()

# HanLP分詞

HanLP = JClass('com.hankcs.hanlp.HanLP')

wordslist = HanLP.segment(raw)

#保存清洗后的數據

wordslist1=str(wordslist).split(",")

# print(wordslist1[1:len(wordslist1)-1])

flagresult=""

# 去除標簽

for v in wordslist1[1:len(wordslist1)-1]:

if "/" in v:

slope=v.index("/")

letter=v[1:slope]

if len(letter)>0 and '\n\u3000\u3000' in letter:

flagresult+="\n"

else:flagresult+=letter +"/" #去除空格

# print(flagresult)

with open(os.path.join(save_folder_path,file),'w',encoding='utf-8') as f:

f.write(flagresult.replace(' /',''))

j += 1

shutdownJVM()

if __name__ == '__main__' :

print('開始進行文本分詞操作：\n')

t1 = time.time()

dealpath="../Database/SogouC/FileTest/"

savepath="../Database/SogouCCut/FileTest/"

# 待分詞的語料類別集根目錄

read_folder_path = '../Database/SogouC/FileNews/'

write_folder_path = '../Database/SogouCCut/'

#jieba中文分詞

CHSegment(read_folder_path,write_folder_path) #300個txtq其中結巴分詞使用3.31秒

HanLPSeg(read_folder_path,write_folder_path) #300個txt其中hanlp分詞使用1.83秒

t2 = time.time()

print('完成中文文本切分: '+str(t2-t1)+"秒。")

運行效果：

總結

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