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小姜机器人,自然语言处理,闲聊机器人,chatbot,中文汉语,特征工程,文本特征,文本相似度,数据增强,同义句生成,句子主干提取

Home Page: https://blog.csdn.net/rensihui

License: MIT License

Python 100.00%

nlp_xiaojiang's Introduction

nlp_xiaojiang

AugmentText

- 回译(效果比较好)
- EDA(同义词替换、插入、交换和删除)(效果还行)
- HMM-marko(质量较差)
- syntax(依存句法、句法、语法书)(简单句还可)
- seq2seq(深度学习同义句生成,效果不理想,seq2seq代码大都是 [https://github.com/qhduan/just_another_seq2seq] 的,效果不理想)

ChatBot

- 检索式ChatBot
    - 像ES那样直接检索(如使用fuzzywuzzy),只能字面匹配
    - 构造句向量,检索问答库,能够检索有同义词的句子
- 生成式ChatBot(todo)
    - seq2seq
    - GAN

FeatureProject

- normalization_util指的是数据归一化
    - 0-1归一化处理
    - 均值归一化
    - sig归一化处理
- sim feature(这里只有ML,没有bert、emlo等的句向量相似度)
    - distance_text_or_vec:各种计算文本、向量距离等
    - distance_vec_TS_SS:TS_SS计算词向量距离
    - cut_td_idf:将小黄鸡语料和gossip结合
    - sentence_sim_feature:计算两个文本的相似度或者距离,例如qq(问题和问题),或者qa(问题和答案)

run(可以在win10下,pycharm下运行)

  • 1.创建tf-idf文件等(运行2需要先跑1):
    python cut_td_idf.py
  • 2.计算两个句子间的各种相似度,先计算一个预定义的,然后可输入自定义的(先跑1):
    python sentence_sim_feature.py
  • 3.chatbot_1跑起来(fuzzy检索-没)(独立):
    python chatbot_fuzzy.py
  • 4.chatbot_2跑起来(句向量检索-词)(独立):
    python chatbot_sentence_vec_by_word.py
  • 5.chatbot_3跑起来(句向量检索-字)(独立):
    python chatbot_sentence_vec_by_char.py
  • 6.数据增强(eda): python enhance_eda.py
  • 7.数据增强(marko): python enhance_marko.py
  • 8.数据增强(translate_account): python translate_tencent_secret.py
  • 9.数据增强(translate_tools): python translate_translate.py
  • 10.数据增强(translate_web): python translate_google.py
  • 11.数据增强(augment_seq2seq): 先跑 python extract_char_webank.py生成数据, 再跑 python train_char_anti.py 然后跑 python predict_char_anti.py

Data

- chinese_vector
    - 截取的部分word2vec训练词向量(自己需要下载全效果才会好)
- corpus
    - 小黄鸡和gossip问答预料(数据没清洗)
    - 微众银行文本相似度匹配比赛的数据,感觉阿里的文本相似度匹配比赛数据更差点
- sentence_vec_encode_char
    - 1.txt(字向量生成的前100000句向量)
- sentence_vec_encode_word
    - 1.txt(词向量生成的前100000句向量)
- tf_idf(chicken_and_gossip.txt生成的tf-idf)

requestments.txt

- python_Levenshtei
    - 调用Levenshtein,我的python是3.6,
    - 打开其源文件: https://www.lfd.uci.edu/~gohlke/pythonlibs/
    - 查找python_Levenshtein-0.12.0-cp36-cp36m-win_amd64.whl下载即可
- pyemd
- pyhanlp
    - 下好依赖JPype1-0.6.3-cp36-cp36m-win_amd64.whl

参考/感谢

其他资料

nlp_xiaojiang's People

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Watchers

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