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SeburSum: a novel set-based summary ranking strategy for summary-level extractive summarization

  • Published:2023-03-20 Issue:12 Volume:79 Page:12949-12977
  • ISSN:0920-8542
  • Container-title:The Journal of Supercomputing
  • language:en
  • Short-container-title:J Supercomput

Author:

Gong Shuai,Zhu Zhenfang,Qi Jiangtao,Wu Wenqing,Tong Chunling

Funder

National Social Science Fund of China

Natural Science Foundation of Shandong Province

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Reference63 articles.

1. Liu Y & Lapata M (2019) Text summarization with pretrained encoders. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) (pp 3730–3740). Association for Computational Linguistics, Hong Kong, China. https://doi.org/10.18653/v1/D19-1387. https://aclanthology.org/D19-1387

2. Wang D, Liu P, Zheng Y, Qiu X, Huang, X (2020) Heterogeneous graph neural networks for extractive document summarization. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp 6209–6219. Association for Computational Linguistics, Online. https://doi.org/10.18653/v1/2020.acl-main.553. https://aclanthology.org/2020.acl-main.553

3. Jia R, Cao Y, Fang F, Zhou Y, Fang Z, Liu Y, Wang S (2021) Deep differential amplifier for extractive summarization. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp 366–376. Association for Computational Linguistics, Online. https://doi.org/10.18653/v1/2021.acl-long.31. https://aclanthology.org/2021.acl-long.31

4. Ruan Q, Ostendorff M, Rehm G (2022) HiStruct+: Improving extractive text summarization with hierarchical structure information. In: Findings of the Association for Computational Linguistics: ACL 2022, pp 1292–1308. Association for Computational Linguistics, Dublin, Ireland. https://doi.org/10.18653/v1/2022.findings-acl.102. https://aclanthology.org/2022.findings-acl.102

5. Xie Q, Bishop JA, Tiwari P, Ananiadou S (2022) Pre-trained language models with domain knowledge for biomedical extractive summarization. Knowl-Based Syst 252:109460

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1. Research on Chinese Text Summarization Methods Based on Topic Filtering;2024 5th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT);2024-03-29
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