def taste_dict(self):
data = model.Taste.get_all()
taste_jieba = jieba.Tokenizer()
for food in data:
taste_jieba.add_word(food['name'], 2000, food['type'])
taste_pseg = pseg.POSTokenizer(taste_jieba)
print('taste_pseg:success init')
return taste_pseg
def foods_dict(self):
data = model.Foods.get_all()
foods_jieba = jieba.Tokenizer()
for food in data:
foods_jieba.add_word(food['name'], 2000, food['type'])
foods_pseg = pseg.POSTokenizer(foods_jieba)
print('foods_pseg:success init')
return foods_pseg
def material_dict(self):
data = model.Material.get_all()
material_jieba = jieba.Tokenizer()
for food in data:
material_jieba.add_word(food['name'], 2000, food['parent_code'])
material_pseg = pseg.POSTokenizer(material_jieba)
print('material_pseg:success init')
return material_pseg
def technics_dict(self):
data = model.Technics.get_all()
technics_jieba = jieba.Tokenizer()
for food in data:
technics_jieba.del_word(food['name'])
# technics_jieba.add_word('是',2000,'ttt')
technics_jieba.add_word(food['name'], 2000, food['type'])
technics_pseg = pseg.POSTokenizer(technics_jieba)
print('technics_pseg:success init')
return technics_pseg
def parse_test(p_str):
''' call jieba module to parse the text with tags, and transform
the respective tag to NLPI forms.
input: text string
output: results with tags
'''
pseg.POSTokenizer(tokenizer=None)
words = pseg.cut(p_str)
ret_str = ''
for word, flag in words:
ret_str += word +'/' + flag + ' '
return ret_str.encode('GB18030')
def __init__(self, model='jieba'):
self.model = model
if model.lower() == 'jieba':
import jieba.posseg as posseg
posseg.initialize()
self.segmentor = posseg.POSTokenizer(tokenizer=None)
elif model.lower() == 'ictclas':
import pynlpir
pynlpir.open()
self.segmentor = pynlpir
else:
raise NotImplementedError
import jieba.posseg as pseg
words = pseg.cut("中国人民是不可战胜的") #词性标注.
words1 = pseg.POSTokenizer(tokenizer=pseg.dt)
for word, flag in words:
print('%s %s' % (word, flag))
print(words1)
# -*- coding: UTF-8 -*-
import sys
import jieba.posseg as pseg
import jieba
import argparse
t = pseg.POSTokenizer()
jieba.initialize()
def segment_nodict(string):
"""
输入为要分词的句子，输出分词后和标注后的结果
:param string: the string that need to be segment
:return: 分词后的结果，用一个列表表示，列表的每一个元素是一个元组，元组第一维表示分好后的词，第二维表示词性。
"""
segment_words = t.cut(string)
segment_list = []
for i in segment_words:
segment_list.append((i.word, i.flag))
return segment_list
if __name__ == '__main__':
with open('jiebapos_union3.txt', 'r') as f:
lines = f.readlines()
str = ''
for index, item in enumerate(lines):
if item != '\n':
word = item.split('\t')[0].strip()
else:
import jieba
from jieba import posseg
from .cmd_tools import tika_convert, antiword_convert
from . import _config
from .data_helps import corpus_cut
__all__ = (
"Files2Text",
"CorpusClean",
"CorpusHandler"
)
jieba.setLogLevel(logging.INFO)
jieba.enable_parallel()
jieba_inst = posseg.POSTokenizer(jieba.Tokenizer())
class ReCache:
N_RE = re.compile(r'\n')
MORE_SPACE_T_RE = re.compile(r'[\s\t]+')
CN_RE = re.compile(r'^[\u4e00-\u9fa5]+$')
class BaseCorpus(object):
def __init__(self, logger=None):
if logger is None:
logging.basicConfig(level=logging.DEBUG,
format=_config.LOG_FORMAT,
datefmt=_config.LOG_DATE_FORMAT)
def __init__(self, dicts=list()):
self.jieba = jieba
# 词典自定义添加了特定词、用户词典、数字词典
self.jieba.add_word("成龙", 1000, 'movie_person')
self.jieba.add_word("快进", 1000)
for k in ['#UNK', '#PAD', '#BOS', '#EOS']:
self.jieba.add_word(k, 1000)
self.jieba.add_word("快进", 1000)
self.jieba.add_word("快进", 1000)
self.jieba.add_word("快进", 1000)
self.jieba.add_word("快进", 1000)
self.jieba.add_word("人民的名义")
self.jieba.add_word("上一页")
self.jieba.add_word("下一页")
self.num_dic = NumDict()
self.num_dic, self.num_array = self.num_dic.get_num_data()
for d in dicts:
self.jieba.load_userdict(d)
logging.debug('Jieba load user dicts: {}'.format(dicts))
data = list()
# 数字
data.append(['上一集', '下一集'])
data.append(self.num_array)
for f in data:
for l in f:
jieba.add_word(l)
# 加载用户自定义词典
db_conf = {
'host': '192.168.11.122',
'port': 3306,
'password': '******',
'user': '******'
}
self.db = pymysql.connect(**db_conf,
charset='utf8mb4',
cursorclass=pymysql.cursors.DictCursor)
# self.db = conf.get_mysql('ailab')
self.seg = jieba.Tokenizer()
self.load_userdict()
# 词典自定义添加了特定词、用户词典、数字词典
self.seg.add_word("成龙", 1000, 'movie_person')
self.seg.add_word("快进", 1000)
for k in ['#UNK', '#PAD', '#BOS', '#EOS']:
self.seg.add_word(k, 1000)
self.seg.add_word("快进", 1000)
self.seg.add_word("快进", 1000)
self.seg.add_word("快进", 1000)
self.seg.add_word("快进", 1000)
self.seg.add_word("人民的名义")
self.seg.add_word("上一页")
self.seg.add_word("下一页")
data = list()
# 数字
data.append(['上一集', '下一集'])
data.append(self.num_array)
for f in data:
for l in f:
self.seg.add_word(l)
self.pos = posseg.POSTokenizer(self.seg)
def __init__(self, threading_pool):
self._save_dir = os.path.join(config.LEARN_PATH, "{user_id}")
self.token = jieba.Tokenizer()
self.pos_token = posseg.POSTokenizer(self.token)
self.threading_pool = threading_pool
self.queue = Queue()
def __init__(self):
self.zt = ["不能", "无法", "没法", "不足", "不了", "不够", "不多", "欠费"] # 21
self.zt1 = ["欠费了", "不够了", "不足了", "停机了"]
self.noaccount_needadd1 = ["充值了", "充了", "充钱了", "冲了", "交了", "充过"] #19
self.noaccount_needadd2 = ["不能", "无法", "没法", "不足", "不了"] #20
self.noaccount_keywords_1 = [
"充", "充值了", "充了", "冲", "冲了", "交了", "充值", "缴费", "交费", "充话费", "交",
"充过"
] #8
self.noaccount_keywords = [
"没显示", "没有显示", "没反应", "没有反应", "没有收到", "没收到", "没增加", "没有增加", "没提示",
"没有提示"
"停机", "打不出去", "还不通", "还欠费", "没到", "没有到", "欠费", "欠", "停机", "不能",
"无法", "没法", "没变", "没钱"
]
self.noaccount_keywords_2 = [
"没到账", "没有到账", "没给充上", "没有充上", "不到账", "未到账", "不进账"
] #10
self.nook_keyword2 = ["有", "还有"]
self.nook_keyword3 = ["钱", "余额", "元"]
self.nook_keyword = [
"只到了", "只到账", "不对", "只有", "只剩", "只", "少了", "不准确", "就剩", "怎么剩",
"就还剩", "应该还剩", "不一致", "不一样", "对不上", "打不出去", "打不通", "不能", "无法",
"没法", "有问题", "有点问题"
] #9
self.nook_keyword1 = ["话费", "余额", "查话费"] #18
self.noaccount_exceptwords = [
"兑换", "流量", "积分", "宽带", "星级", "游戏", "电子券", "活动", "发票", "充错", "会员",
"打印发票", "送"
]
self.noaccount_keywords_3 = [
"微信公众号", "公众号", "app", "客户端", "掌厅", "掌上营业厅"
] #17
self.huafei_1 = ["充", "交", "冲", "冲话费", "充流量", "充话费", "充值", "充钱",
"缴费"] #1
self.huafei_2 = [
"方法", "哪里", "怎么", "方式", "如何", "渠道", "我想", "我要", "想", "要", "咋", "怎样"
] #2
self.huafei_3 = [
"发票", "开发票", "q", "qb", "qq币", "qq", "打印发票", "记录", "电费", "座机",
"固定电话", "会员", "扣币"
] #3
self.huafei_4 = [
"刚", "刚刚", "积分", "宽带", "星级", "游戏", "电子券", "活动", "兑换", "固话", "开机",
"漫游", "语音", "扣", "账单", "明细", "详单"
] #16
self.huafei_5 = ["知道", "了解"]
self.yue_1 = ["查", "查询"] #11
self.yue_2 = ["话费", "钱", "余额"] #12
self.yue_3 = ["剩", "剩余", "有多少", "还有多少"] #13
self.yue_4 = ["查话费", "余额"] #14
self.tkz = jieba.Tokenizer()
from answers.word_dictionary import Dictionary
for i in Dictionary.meword:
elem = i.split(' ')
if len(elem) == 1:
self.tkz.add_word(i)
elif len(elem) == 2:
self.tkz.add_word(elem[0], tag=elem[1])
else:
self.tkz.add_word(elem[0], tag=elem[2], freq=int(elem[1]))
# self.tkz.load_userdict("meword")
self.psegp = pseg.POSTokenizer(self.tkz)
import jieba.posseg as pseg
import jieba
data = open("data.txt", "r")
result = open("result.txt", "w")
pos = pseg.POSTokenizer(jieba.Tokenizer(dictionary='dict.txt.big'))
for line in data:
words = pos.cut(line)
for word, flag in words:
result.write('%s\%s ' % (word, flag))
break
data.close()
result.close()
words = pos.cut('我的老师说：“我们大家都是好孩子，好孩子应该看《好书》”')
for word, flag in words:
print('%s %s' % (word, flag))
def __init__(self, user_dict: Union[str, Iterable] = None):
self.t = posseg.POSTokenizer()
self.t.initialize()
self.trie = Trie()
if user_dict:
self.load_user_dict(user_dict)
import glob
import math
import json
import jieba
from jieba import posseg
token = jieba.Tokenizer()
file = glob.glob("./../jieba_dict/*.txt")
for fp in file:
token.load_userdict(fp)
pos_token = posseg.POSTokenizer(token)
file = glob.glob("./*.txt")
item_ids = 0
sentence_ids = 0 # 句子条目
word_bag = set()
PMI_DICT = {} # key(wj,wi),value log(P(wi|wj)/p(wi))
WI = {}
for fp in file:
for line in open(fp, "r", encoding="utf-8"):
line_list = line.strip().split("####")
if len(line_list) != 3:
continue
query, response, sentiment = line_list
sentence_ids += 1
query_token = [word for word, tag in pos_token.lcut(query) if "n" in tag]
for to in query_token:
word_bag.add(to)
response_token = [word for word, tag in pos_token.lcut(response) if "n" in tag]
for to in response_token:
WI[to] = WI.get(to, 0) + 1
word_bag.add(to)