科研成果详情

题名LenC: A redundancy-aware length control framework for extractive summarization
作者
发表日期2021-08-20
会议名称2021 4th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)
会议录名称2021 4th International Conference on Pattern Recognition and Artificial Intelligence (PRAI 2021)
ISBN9781665413220
页码1-7
会议日期August 20-22, 2021
会议地点Yibin, China
出版者The Institute of Electrical and Electronics Engineers, Inc.
摘要

While extractive summarization is an important approach of the NLP text summarization task, redundancy in the generated extractive summary is always a problem. Previous works usually set the length of the output summary to a fixed number, which might only be appropriate for some of the documents while too long for others. At the same time, though extractive summarization possesses high readability as it directly selects sentences from the document, the unimportant parts within sentences are also selected. These two scenarios result in redundancy in the extractive summaries. To solve this problem, we propose a length control framework for extractive summarization, named LenC, in a two-stage pipeline. We first use a pretrained BERT-based summarizer to select smaller units (i.e. EDUs) than original sentences to abandon the insignificant parts of a sentence. Then a portable length controller is implemented to prune the output summary to an appropriate length, and it can be attached to any extractive summarizer. Experiments show that the proposed model outperforms the state-of-the-art baseline models and successfully reduces the redundancy in the extractive summaries.

关键词Redundant information Single document summarization
DOI10.1109/PRAI53619.2021.9550801
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语种英语English
Scopus入藏号2-s2.0-85117897473
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被引频次[WOS]:0   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/6838
专题理工科技学院
作者单位
1.BNU-HKBU United International College,Computer Science and Technology,Guangdong,China
2.Hong Kong Baptist University,Computer Science and Technology,Hong Kong,China
第一作者单位北师香港浸会大学
推荐引用方式
GB/T 7714
Li, Shuxin,Su, Weifeng,Liu, Jiming. LenC: A redundancy-aware length control framework for extractive summarization[C]: The Institute of Electrical and Electronics Engineers, Inc., 2021: 1-7.
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