language:
- en
paperswithcode_id: web-of-science-dataset
pretty_name: Web of Science Dataset
dataset_info:
- config_name: WOS5736
features:
- name: input_data
dtype: string
- name: label
dtype: int32
- name: label_level_1
dtype: int32
- name: label_level_2
dtype: int32
splits:
- name: train
num_bytes: 8051533
num_examples: 5736
download_size: 60222421
dataset_size: 8051533
- config_name: WOS11967
features:
- name: input_data
dtype: string
- name: label
dtype: int32
- name: label_level_1
dtype: int32
- name: label_level_2
dtype: int32
splits:
- name: train
num_bytes: 16248391
num_examples: 11967
download_size: 60222421
dataset_size: 16248391
- config_name: WOS46985
features:
- name: input_data
dtype: string
- name: label
dtype: int32
- name: label_level_1
dtype: int32
- name: label_level_2
dtype: int32
splits:
- name: train
num_bytes: 65471726
num_examples: 46985
download_size: 60222421
dataset_size: 65471726
Dataset Card for "web_of_science"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://data.mendeley.com/datasets/9rw3vkcfy4/6
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 180.67 MB
- Size of the generated dataset: 89.81 MB
- Total amount of disk used: 270.48 MB
Dataset Summary
Copyright (c) 2017 Kamran Kowsari
Permission is hereby granted, free of charge, to any person obtaining a copy of this dataset and associated documentation files (the "Dataset"), to deal in the dataset without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Dataset, and to permit persons to whom the dataset is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Dataset.
If you use this dataset please cite: Referenced paper: HDLTex: Hierarchical Deep Learning for Text Classification
Description of Dataset:
Here is three datasets which include WOS-11967 , WOS-46985, and WOS-5736 Each folder contains: -X.txt -Y.txt -YL1.txt -YL2.txt
X is input data that include text sequences Y is target value YL1 is target value of level one (parent label) YL2 is target value of level one (child label) Web of Science Dataset WOS-5736 -This dataset contains 5,736 documents with 11 categories which include 3 parents categories.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
WOS11967
- Size of downloaded dataset files: 60.22 MB
- Size of the generated dataset: 16.25 MB
- Total amount of disk used: 76.48 MB
An example of 'train' looks as follows.
WOS46985
- Size of downloaded dataset files: 60.22 MB
- Size of the generated dataset: 65.50 MB
- Total amount of disk used: 125.72 MB
An example of 'train' looks as follows.
WOS5736
- Size of downloaded dataset files: 60.22 MB
- Size of the generated dataset: 8.05 MB
- Total amount of disk used: 68.27 MB
An example of 'train' looks as follows.
Data Fields
The data fields are the same among all splits.
WOS11967
input_data
: astring
feature.label
: aint32
feature.label_level_1
: aint32
feature.label_level_2
: aint32
feature.
WOS46985
input_data
: astring
feature.label
: aint32
feature.label_level_1
: aint32
feature.label_level_2
: aint32
feature.
WOS5736
input_data
: astring
feature.label
: aint32
feature.label_level_1
: aint32
feature.label_level_2
: aint32
feature.
Data Splits
name | train |
---|---|
WOS11967 | 11967 |
WOS46985 | 46985 |
WOS5736 | 5736 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@inproceedings{kowsari2017HDLTex,
title={HDLTex: Hierarchical Deep Learning for Text Classification},
author={Kowsari, Kamran and Brown, Donald E and Heidarysafa, Mojtaba and Jafari Meimandi, Kiana and and Gerber, Matthew S and Barnes, Laura E},
booktitle={Machine Learning and Applications (ICMLA), 2017 16th IEEE International Conference on},
year={2017},
organization={IEEE}
}
Contributions
Thanks to @thomwolf, @lhoestq, @mariamabarham, @lewtun for adding this dataset.