meliascosta/wiki_academic_subjects

---
license: cc-by-3.0
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- crowdsourced
multilinguality:
- monolingual
paperswithcode_id: wikitext-2
pretty_name: Wikipedia Outline of Academic Disciplines
size_categories:
- 10K<n<100K
source_datasets:
- original
tags:
- hierarchical
- academic
- tree
- dag
- topics
- subjects
task_categories:
- text-classification
task_ids:
- multi-label-classification
---

# Dataset Card for Wiki Academic Disciplines`

## Table of Contents
- [Table of Contents](#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:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

This dataset was created from the [English wikipedia](https://meta.wikimedia.org/wiki/Data_dump_torrents#English_Wikipedia) dump of January 2022.
The main goal was to train a hierarchical classifier of academic subjects using [HiAGM](https://github.com/Alibaba-NLP/HiAGM).

### Supported Tasks and Leaderboard

Text classification - No leaderboard at the moment.

### Languages

English

## Dataset Structure

The dataset consists of groups of labeled text chunks (tokenized by spaces and with stopwords removed).
Labels are organized in a hieararchy (a DAG with a special Root node) of academic subjects.
Nodes correspond to entries in the [outline of academic disciplines](https://en.wikipedia.org/wiki/Outline_of_academic_disciplines) article from Wikipedia.

### Data Instances

Data is split in train/test/val each on a separate `.jsonl` file. Label hierarchy is listed a as TAB separated adjacency list on a `.taxonomy` file.
### Data Fields

JSONL files contain only two fields: a "token" field which holds the text tokens and a "label" field which holds a list of labels for that text.

### Data Splits

80/10/10 TRAIN/TEST/VAL schema

## Dataset Creation

All texts where extracted following the linked articles on [outline of academic disciplines](https://en.wikipedia.org/wiki/Outline_of_academic_disciplines)

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

Wiki Dump

#### Who are the source language producers?

Wikipedia community.

### Annotations

#### Annotation process

Texts where automatically assigned to their linked academic discipline

#### Who are the annotators?

Wikipedia Community.

### Personal and Sensitive Information

All information is public.

## Considerations for Using the Data

### Social Impact of Dataset

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

Creative Commons 3.0 (see [Wikipedia:Copyrights](https://en.wikipedia.org/wiki/Wikipedia:Copyrights))

### Citation Information

1. Zhou, Jie, et al. "Hierarchy-aware global model for hierarchical text classification." Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020.

### Contributions

Thanks to [@meliascosta](https://github.com/meliascosta) for adding this dataset.

原始信息汇总

数据集概述

数据集名称

• 名称: Wikipedia Outline of Academic Disciplines
• 别名: Wiki Academic Disciplines

数据集基本信息

• 许可证: CC-BY-3.0
• 语言: 英语
• 多语言性: 单语种
• 大小: 10K<n<100K
• 来源: 原始数据
• 任务类别: 文本分类
• 任务ID: 多标签分类

数据集描述

• 摘要: 该数据集源自2022年1月英语维基百科的转储，主要用于训练学术科目层次分类器，使用HiAGM方法。
• 支持任务: 文本分类，目前无排行榜。
• 结构: 数据集包含标记的文本块，标签组织为学术科目的层次结构（特殊根节点的DAG）。

数据集结构

• 数据实例: 数据分为训练/测试/验证集，分别存储在.jsonl文件中，标签层次结构存储在.taxonomy文件中。
• 数据字段: JSONL文件包含两个字段："token"（文本令牌）和"label"（文本标签列表）。
• 数据分割: 遵循80/10/10的训练/测试/验证分割。

数据集创建

• 来源数据: 从维基百科转储中提取，遵循学术科目概述文章的链接。
• 注释过程: 文本自动分配到其链接的学术科目。
• 注释者: 维基百科社区。

许可证信息

• 许可证: 创意共享3.0许可证（参考维基百科版权信息）

引用信息

• 引用文献: Zhou, Jie, et al. "Hierarchy-aware global model for hierarchical text classification." Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020.