# cMedQA2
This is updated version of the dataset for Chinese community medical question answering. The dataset is in version 2.0 and is available for non-commercial research. We will update and expand the database from time to time. In order to protect the privacy, the data is anonymized and no personal information is included.
The older version of cMedQA is v1.0. You can [click here](https://github.com/zhangsheng93/cMedQA)
# Overview
| DataSet | #Ques | #Ans | Ave. #words per Question | Ave. #words per Answer| Ave. #characters per Question | Ave. #characters per Answer |
| :-: | :-: | :-: | :-: | :-: | :-: | :-: |
|Train|100,000|188,490|-|-|48|101|
|Dev|4,000|7,527|-|-|49|101|
|Test|4,000|7,552|-|-|49|100|
|Total|108,000|203,569|-|-|49|101|
* **questions.csv** All Questions and their content.
* **answers.csv** All Answers and their content.
* **train_candidates.txt** **dev_candidates.txt** **test_candidates.txt** The split of training set, development set and test set respectively.
# Paper
**Multi-Scale Attentive Interaction Networks for Chinese Medical Question Answer Selection.** [link to the paper](https://ieeexplore.ieee.org/abstract/document/8548603)
Please cite our paper when you use the dataset.
```
@ARTICLE{8548603,
author={S. Zhang and X. Zhang and H. Wang and L. Guo and S. Liu},
journal={IEEE Access},
title={Multi-Scale Attentive Interaction Networks for Chinese Medical Question Answer Selection},
year={2018},
volume={6},
number={},
pages={74061-74071},
keywords={Biomedical imaging;Data mining;Semantics;Medical services;Feature extraction;Knowledge discovery;Medical question answering;interactive attention;deep learning;deep neural networks},
doi={10.1109/ACCESS.2018.2883637},
ISSN={2169-3536},
month={},}
```
基于sqlite数据库以及深度学习lstm实现的检索式聊天机器人python源码+数据集+模型+代码注释.zip
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基于sqlite数据库以及深度学习lstm实现的检索式聊天机器人python源码+数据集+模型+代码注释.zip （41个子文件） 
code 
bp_convert.py 7KB running model bidirectional_lstm checkpoint 175B bidirectional_lstm.ckpt-6800.index 2KB bidirectional_lstm.ckpt-6700.index 2KB bidirectional_lstm.ckpt-6800.data-00000-of-00001 17.95MB bidirectional_lstm.ckpt-6700.meta 1.43MB bidirectional_lstm.ckpt-6800.meta 1.43MB bidirectional_lstm.ckpt-6700.data-00000-of-00001 17.95MB graph bidirectional_lstm train events.out.tfevents.1640423321.DESKTOP-MLERUN1 2.61MB events.out.tfevents.1640424047.DESKTOP-MLERUN1 3.33MB dev events.out.tfevents.1640424053.DESKTOP-MLERUN1 2.59MB events.out.tfevents.1640423325.DESKTOP-MLERUN1 2.59MB demo answer_data_sqlite3.py 2KB answer_data_mysql.py 1KB chat_robot_wep_api_demo.py 775B 问答对数据转换_数据库.py 714B sqllite3_demo.py 2KB utils __init__.py 0B data_help.py 11KB __pycache__ data_help.cpython-37.pyc 7KB __init__.cpython-37.pyc 194B net bidirectional_lstm.py 4KB __pycache__ text_cnn_lstm.cpython-37.pyc 4KB bidirectional_lstm.cpython-37.pyc 3KB bp_demo.py 2KB similarity_data dev.csv 725KB train_1.csv 483B train.csv 7.11MB test.csv 728KB train_similarity_model.py 24KB que_ans_data q_a_data.csv 0B LICENSE 38KB question.csv 17.35MB answer.csv 68.29MB README.md 2KB search_chat_robot.py 25KB README.md 4B config __init__.py 0B
stop_word.txt 5KB mapping_file.pkl 152KB bidirectional_lstm.pb 6.11MB资源评论
