参考：
metadata
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:cord19/metadata')
- 说明：
The Covid-19 Open Research Dataset (CORD-19) is a growing resource of scientific papers on Covid-19 and related
historical coronavirus research. CORD-19 is designed to facilitate the development of text mining and information
retrieval systems over its rich collection of metadata and structured full text papers. Since its release, CORD-19
has been downloaded over 75K times and has served as the basis of many Covid-19 text mining and discovery systems.
The dataset itself isn't defining a specific task, but there is a Kaggle challenge that define 17 open research
questions to be solved with the dataset: https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge/tasks
- 许可：无已知许可
- 版本：0.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'train' |
368618 |
- 特征：
{
"cord_uid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sha": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_x": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"doi": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"abstract": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"publish_time": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"authors": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"journal": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
fulltext
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:cord19/fulltext')
- 说明：
The Covid-19 Open Research Dataset (CORD-19) is a growing resource of scientific papers on Covid-19 and related
historical coronavirus research. CORD-19 is designed to facilitate the development of text mining and information
retrieval systems over its rich collection of metadata and structured full text papers. Since its release, CORD-19
has been downloaded over 75K times and has served as the basis of many Covid-19 text mining and discovery systems.
The dataset itself isn't defining a specific task, but there is a Kaggle challenge that define 17 open research
questions to be solved with the dataset: https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge/tasks
- 许可：无已知许可
- 版本：0.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'train' |
368618 |
- 特征：
{
"cord_uid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sha": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_x": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"doi": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"abstract": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"publish_time": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"authors": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"journal": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"fulltext": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
embeddings
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:cord19/embeddings')
- 说明：
The Covid-19 Open Research Dataset (CORD-19) is a growing resource of scientific papers on Covid-19 and related
historical coronavirus research. CORD-19 is designed to facilitate the development of text mining and information
retrieval systems over its rich collection of metadata and structured full text papers. Since its release, CORD-19
has been downloaded over 75K times and has served as the basis of many Covid-19 text mining and discovery systems.
The dataset itself isn't defining a specific task, but there is a Kaggle challenge that define 17 open research
questions to be solved with the dataset: https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge/tasks
- 许可：无已知许可
- 版本：0.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'train' |
368618 |
- 特征：
{
"cord_uid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sha": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_x": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"doi": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"abstract": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"publish_time": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"authors": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"journal": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"doc_embeddings": {
"feature": {
"dtype": "float64",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}