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컬렉션을 사용해 정리하기
내 환경설정을 기준으로 콘텐츠를 저장하고 분류하세요.
약 400만 개의 기사로 구성된 Gigaword의 기사 쌍 코퍼스에서 헤드라인 생성. https://github.com/harvardnlp/sent-summary 와 동일하지만 형식이 더 나은 https://github.com/microsoft/unilm/ 에서 제공하는 'org_data'를 사용합니다.
두 가지 기능이 있습니다. - 문서: 기사. - 요약: 제목.
| 나뉘다 | 예 |
|---|
'test' | 1,951 |
'train' | 3,803,957 |
'validation' | 189,651 |
FeaturesDict({
'document': Text(shape=(), dtype=string),
'summary': Text(shape=(), dtype=string),
})
| 특징 | 수업 | 모양 | D타입 | 설명 |
|---|
| 풍모Dict | | | |
| 문서 | 텍스트 | | 끈 | |
| 요약 | 텍스트 | | 끈 | |
@article{graff2003english,
title={English gigaword},
author={Graff, David and Kong, Junbo and Chen, Ke and Maeda, Kazuaki},
journal={Linguistic Data Consortium, Philadelphia},
volume={4},
number={1},
pages={34},
year={2003}
}
@article{Rush_2015,
title={A Neural Attention Model for Abstractive Sentence Summarization},
url={http://dx.doi.org/10.18653/v1/D15-1044},
DOI={10.18653/v1/d15-1044},
journal={Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing},
publisher={Association for Computational Linguistics},
author={Rush, Alexander M. and Chopra, Sumit and Weston, Jason},
year={2015}
}
달리 명시되지 않는 한 이 페이지의 콘텐츠에는 Creative Commons Attribution 4.0 라이선스에 따라 라이선스가 부여되며, 코드 샘플에는 Apache 2.0 라이선스에 따라 라이선스가 부여됩니다. 자세한 내용은 Google Developers 사이트 정책을 참조하세요. 자바는 Oracle 및/또는 Oracle 계열사의 등록 상표입니다.
최종 업데이트: 2022-12-06(UTC)
[null,null,["최종 업데이트: 2022-12-06(UTC)"],[],[],null,["# gigaword\n\n\u003cbr /\u003e\n\n- **Description**:\n\nHeadline-generation on a corpus of article pairs from Gigaword consisting of\naround 4 million articles. Use the 'org_data' provided by\n\u003chttps://github.com/microsoft/unilm/\u003e which is identical to\n\u003chttps://github.com/harvardnlp/sent-summary\u003e but with better format.\n\nThere are two features: - document: article. - summary: headline.\n\n- **Homepage** :\n \u003chttps://github.com/harvardnlp/sent-summary\u003e\n\n- **Source code** :\n [`tfds.summarization.Gigaword`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/summarization/gigaword.py)\n\n- **Versions**:\n\n - **`1.2.0`** (default): No release notes.\n- **Download size** : `551.61 MiB`\n\n- **Dataset size** : `1.02 GiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n No\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|-----------|\n| `'test'` | 1,951 |\n| `'train'` | 3,803,957 |\n| `'validation'` | 189,651 |\n\n- **Feature structure**:\n\n FeaturesDict({\n 'document': Text(shape=(), dtype=string),\n 'summary': Text(shape=(), dtype=string),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|----------|--------------|-------|--------|-------------|\n| | FeaturesDict | | | |\n| document | Text | | string | |\n| summary | Text | | string | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `('document', 'summary')`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Examples**\n ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\n- **Citation**:\n\n @article{graff2003english,\n title={English gigaword},\n author={Graff, David and Kong, Junbo and Chen, Ke and Maeda, Kazuaki},\n journal={Linguistic Data Consortium, Philadelphia},\n volume={4},\n number={1},\n pages={34},\n year={2003}\n }\n\n @article{Rush_2015,\n title={A Neural Attention Model for Abstractive Sentence Summarization},\n url={http://dx.doi.org/10.18653/v1/D15-1044},\n DOI={10.18653/v1/d15-1044},\n journal={Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing},\n publisher={Association for Computational Linguistics},\n author={Rush, Alexander M. and Chopra, Sumit and Weston, Jason},\n year={2015}\n }"]]
