tarudesu/ViHealthQA

---
task_categories:
- question-answering
language:
- vi
tags:
- medical
pretty_name: Vietnamese Healthcare Question Answering Dataset
size_categories:
- 10K<n<100K
---
## Disclaimer:
The dataset may contain personal information crawled along with the contents of various sources. Please make a filter in pre-processing data before starting your research training.

# SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts
This is the official repository for the ViHealthQA dataset from the paper [SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts](https://arxiv.org/pdf/2206.09600.pdf), which was accepted at the [KSEM-2022](https://ksem22.smart-conf.net/index.html).

# Citation Information
The provided dataset is only used for research purposes!

```
@InProceedings{nguyen2022viheathqa,
author="Nguyen, Nhung Thi-Hong
and Ha, Phuong Phan-Dieu
and Nguyen, Luan Thanh
and Van Nguyen, Kiet
and Nguyen, Ngan Luu-Thuy",
title="SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts",
booktitle="Knowledge Science, Engineering and Management",
year="2022",
publisher="Springer International Publishing",
address="Cham",
pages="371--382",
isbn="978-3-031-10986-7"
}

```

# Abstract

Question answering (QA) systems have gained explosive attention in recent years. However, QA tasks in Vietnamese do not have many datasets. Significantly, there is mostly no dataset in the medical domain. Therefore, we built a Vietnamese Healthcare Question Answering dataset (ViHealthQA), including 10,015 question-answer passage pairs for this task, in which questions from health-interested users were asked on prestigious health websites and answers from highly qualified experts. This paper proposes a two-stage QA system based on Sentence-BERT (SBERT) using multiple negatives ranking (MNR) loss combined with BM25. Then, we conduct diverse experiments with many bag-of-words models to assess our system’s performance. With the obtained results, this system achieves better performance than traditional methods.

# Dataset
The ViHealthQA dataset is consist of 10,015 question-answer passage pairs. Note that questions are from health-interested users asked on prestigious health websites and answers are from highly qualified experts.

The dataset is divided into three parts as below:
1. Train set: 7.01K question-answer pairs
2. Valid set: 2.01 question-answer pairs
3. Test set: 993 question-answer pairs

# Contact
Please feel free to contact us by email [e-mail] if you have any further information!

任务类别：
- 问答（Question Answering, QA）
语言：
- 越南语
标签：
- 医疗（Medical）
数据集名称：越南医疗问答数据集（Vietnamese Healthcare Question Answering Dataset）
规模类别：
- 10K<n<100K
---

## 免责声明：
本数据集可能包含随各类来源内容一同爬取得到的个人信息，请在开展研究训练前于数据预处理阶段进行过滤。

# SPBERTQA：基于句子Transformer（Sentence Transformers）的医疗文本两阶段问答系统
本仓库为发表于KSEM-2022的论文《SPBERTQA：基于句子Transformer（Sentence Transformers）的医疗文本两阶段问答系统》配套的ViHealthQA数据集官方仓库，论文链接：https://arxiv.org/pdf/2206.09600.pdf，KSEM-2022会议官网：https://ksem22.smart-conf.net/index.html。

# 引用信息
本数据集仅可用于学术研究用途！

@InProceedings{nguyen2022viheathqa,
author="Nguyen, Nhung Thi-Hong
and Ha, Phuong Phan-Dieu
and Nguyen, Luan Thanh
and Van Nguyen, Kiet
and Nguyen, Ngan Luu-Thuy",
title="SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts",
booktitle="Knowledge Science, Engineering and Management",
year="2022",
publisher="Springer International Publishing",
address="Cham",
pages="371--382",
isbn="978-3-031-10986-7"
}

# 摘要
问答（Question Answering, QA）系统近年来受到了爆发式关注。然而，越南语的问答任务数据集较为匮乏，医疗领域的问答数据集更是几乎空白。为此，我们构建了越南医疗问答数据集（ViHealthQA），该数据集包含10015条问答段落对，其中问题来自于知名健康网站上用户提出的健康相关咨询，答案则由资深医疗专家提供。本文提出了一种基于句子BERT（Sentence-BERT, SBERT）的两阶段问答系统，结合了多重负样本排序（Multiple Negatives Ranking, MNR）损失函数与BM25算法。随后，我们使用多种词袋（Bag-of-Words）模型开展了多样的实验以评估该系统的性能。实验结果表明，该系统的表现优于传统方法。

# 数据集
ViHealthQA数据集共包含10015条问答段落对。需注意，问题来自于知名健康网站上用户提出的健康相关咨询，答案由资深医疗专家提供。
本数据集分为以下三个部分：
1. 训练集：7010条问答对
2. 验证集：2010条问答对
3. 测试集：993条问答对

# 联系方式
若需进一步咨询，请通过邮箱 [e-mail] 与我们联系！

原始信息汇总

数据集概述

基本信息

• 任务类别: 问答系统
• 语言: 越南语
• 标签: 医疗
• 数据集名称: Vietnamese Healthcare Question Answering Dataset
• 数据集大小: 10K<n<100K

数据集描述

• 数据集内容: 包含10,015个问答对，问题来自关注健康的用户在知名健康网站上的提问，答案来自高资质专家。
• 数据集划分:
  1. 训练集: 7,010个问答对
  2. 验证集: 2,010个问答对
  3. 测试集: 993个问答对

引用信息

@InProceedings{nguyen2022viheathqa, author="Nguyen, Nhung Thi-Hong and Ha, Phuong Phan-Dieu and Nguyen, Luan Thanh and Van Nguyen, Kiet and Nguyen, Ngan Luu-Thuy", title="SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts", booktitle="Knowledge Science, Engineering and Management", year="2022", publisher="Springer International Publishing", address="Cham", pages="371--382", isbn="978-3-031-10986-7" }