embedding-data/Amazon-QA

---
license: mit
language:
- en
paperswithcode_id: embedding-data/Amazon-QA
pretty_name: Amazon-QA
task_categories:
- sentence-similarity
- paraphrase-mining
task_ids:
- semantic-similarity-classification
---

# Dataset Card for "Amazon-QA"

## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)

## Dataset Description

- **Homepage:** [http://jmcauley.ucsd.edu/data/amazon/qa/](http://jmcauley.ucsd.edu/data/amazon/qa/)
- **Repository:** [More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [Julian McAuley](https://cseweb.ucsd.edu//~jmcauley/#)
- **Size of downloaded dataset files:**
- **Size of the generated dataset:**
- **Total amount of disk used:** 247 MB

### Dataset Summary

This dataset contains Question and Answer data from Amazon.

Disclaimer: The team releasing Amazon-QA did not upload the dataset to the Hub and did not write a dataset card.
These steps were done by the Hugging Face team.

### Supported Tasks
- [Sentence Transformers](https://huggingface.co/sentence-transformers) training; useful for semantic search and sentence similarity.
### Languages
- English.
## Dataset Structure
Each example in the dataset contains pairs of query and answer sentences and is formatted as a dictionary:
```
{"query": [sentence_1], "pos": [sentence_2]}
{"query": [sentence_1], "pos": [sentence_2]}
...
{"query": [sentence_1], "pos": [sentence_2]}
```
This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar sentences.
### Usage Example
Install the 🤗 Datasets library with `pip install datasets` and load the dataset from the Hub with:
```python
from datasets import load_dataset
dataset = load_dataset("embedding-data/Amazon-QA")
```
The dataset is loaded as a `DatasetDict` and has the format:
```python
DatasetDict({
train: Dataset({
features: ['query', 'pos'],
num_rows: 1095290
})
})
```
Review an example `i` with:
```python
dataset["train"][0]
```
### Data Instances

### Data Fields

### Data Splits

## Dataset Creation

### Curation Rationale

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

#### Who are the source language producers?

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

### Annotations

#### Annotation process

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

#### Who are the annotators?

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

### Personal and Sensitive Information

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

### Discussion of Biases

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

### Other Known Limitations

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/s)

## Additional Information

### Dataset Curators

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

### Licensing Information

[More Information Needed](http://jmcauley.ucsd.edu/data/amazon/qa/)

### Citation Information

### Contributions

原始信息汇总

数据集概述：Amazon-QA

数据集描述

数据集总结

• 内容: 包含来自亚马逊的问题和回答数据。
• 用途: 用于训练Sentence Transformers模型，适用于语义搜索和句子相似性分析。

支持的任务

• 任务: Sentence Transformers训练。
• 应用: 语义搜索和句子相似性。

语言

• 语言: 英语。

数据集结构

数据实例

• 格式: 每个实例包含查询和回答句子的配对，格式为字典。

• 示例:

  {"query": [sentence_1], "pos": [sentence_2]}

数据字段

• 字段: query 和 pos。

数据分割

• 分割: 数据集被加载为DatasetDict，包含训练集。
• 示例: python DatasetDict({ train: Dataset({ features: [query, pos], num_rows: 1095290 }) })

数据集创建

来源数据

• 初始数据收集和标准化: 信息待补充。
• 源语言生产者: 信息待补充。

注释

• 注释过程: 信息待补充。
• 注释者: 信息待补充。

个人和敏感信息

• 处理: 信息待补充。

使用数据的考虑

数据集的社会影响

• 影响: 信息待补充。

偏见讨论

• 偏见: 信息待补充。

其他已知限制

• 限制: 信息待补充。

附加信息

数据集管理员

• 管理员: 信息待补充。

许可信息

• 许可: MIT。

引用信息

• 引用: 信息待补充。

贡献

• 贡献: 信息待补充。