A Large-Scale Chinese Long-text Extractive Summarization Corpus
Kai Chen, Guanyu Fu, Qingcai Chen, Baotian Hu
ckai.hit@gmail.com, fuguanyu0214@gmail.com, qingcai.chen@hit.edu.cn, hubaotian@hit.edu.cn
Introduction:
Recently, large-scale datasets have vastly facilitated the development in nearly domains of Natural Language Processing. However, lacking large scale Chinese corpus is still a critical bottleneck for further research on deep text summarization methods. In this paper, we publish a large-scale Chinese Long-text Extractive Summarization corpus named CLES. The CLES contains about 104K <summary, article> pairs, which is originally collected from Sina Weibo\footnote{Sina Weibo is a famous Chinese social media platform in China like Twitter, and the website of it is: WWW.weibo.com. And this corpus is only used for academic research.}. To verify the quality of the corpus, we also manually tagged the relevance score of 5,000 <summary, article> pairs. Our benchmark models on the proposed corpus include conventional deep learning based extractive models and several pre-trained Bert-based algorithms. Their performances are reported and briefly analyzed to facilitate further research on the corpus.
Download:
If you want to acquire the corpus. Please fill the application form and send it to Qingcai Chen: qingcai.chen@hit.edu.cn or Kai Chen: ckai.hit@gmail.com [Application from]
How to cite the CLES corpus:
This website accompanies our paper:
Chen K, Fu G, Chen Q, Baotian Hu. A Large-Scale Chinese Long-Text Extractive Summarization Corpus[C]//ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021: 7828-7832.. [full text] [bib]
Copyright Notice:
1. Respect the privacy of personal information of the original source.
2. The original copyright of all the data of the CLES: A Large-scale Chinese Long-text Extractive Summarization Corpus belongs to writers on Sina Weibo. Intelligent Computing Research Center, Harbin Institute of Technology (Shenzhen) collects, organizes, filters and purifies them. CLES is free to the public for academic research.
3. If you want to use the dataset for further research, data providers, Intelligent Computing Research Center, Harbin Institute of Technology (Shenzhen), should be identified in your results.
4. The dataset is only for the specified applicant or study groups for research purposes. Without permission, it may not be used for any commercial purposes.
5. If the terms changed, the latest online version shall prevail.
