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Datasets:
nicolauduran45
/
scidocs-keywords-exkeyliword

Tasks:
Text Generation
Text2Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
1M - 10M
Tags:
keyword-generation
Science
Research
Academia
Innovation
Technology
Libraries:
Datasets
Dask
License:
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scidocs-keywords-exkeyliword / README.md
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metadata
license: apache-2.0
task_categories:
  - text-generation
  - text2text-generation
language:
  - en
tags:
  - keyword-generation
  - Science
  - Research
  - Academia
  - Innovation
  - Technology
pretty_name: scientific papers with their author keywords
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
dataset_info:
  features:
    - name: title
      dtype: string
    - name: abstract
      dtype: string
    - name: keywords
      dtype: string
    - name: source_name
      dtype: string
  splits:
    - name: train
      num_bytes: 2771926367
      num_examples: 2640662
  download_size: 1603171250
  dataset_size: 2771926367

SciDocs Keywords exKEYliWORD

Dataset Description

SciDocs2Keywords is a dataset consisting of scientific papers (title and abstract) and their associated author-provided keywords. It is designed for use in task of keyword extraction or abstraction.

Each entry in the dataset includes:

  • Title: The title of the scientific paper.
  • Abstract: A brief summary of the paper.
  • Author Keywords: Keywords provided by the authors to highlight the main topics or concepts of the paper.
  • Source: Paper provider source API.

Associated Model

soon...

How to Use

To use this dataset for model training or evaluation, you can load it using the Hugging Face datasets library as follows:

from datasets import load_dataset

dataset = load_dataset("nicolauduran45/scidocs-keywords-exkeyliword")
print(dataset[0])