Research on Chinese summary generation based on pointer key information

Wenming Huang; Xianghui Bu; Yannan Xiao; Yayuan Wen; Zhenrong Deng

doi:10.1117/12.2656552

20 October 2022 Research on Chinese summary generation based on pointer key information

Wenming Huang, Xianghui Bu, Yannan Xiao, Yayuan Wen, Zhenrong Deng

Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 124512J (2022) https://doi.org/10.1117/12.2656552
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China

Abstract

Sequence-to-sequence models provide a feasible new approach for generative text summarization, but these models are not able to accurately reproduce factual details and subject information. To address the problem of unconstrained and uncontrollable content generation of generative text summarization models, this paper proposes a generative summarization method KGIT that uses Transformer as a skeleton and incorporates both BERT pre-training model and keyword information. The model uses a comprehensive keyword extraction algorithm, uses two results extracted by LSTM and TextRank as vocabularies respectively, and uses pointers keywords are selected and the extracted keywords are used as the guiding information to generate the summary based on the guiding information. KGIT model can associate the source text and keywords to avoid generating a summary of irrelevant topics. The ROUGE value is used as the evaluation criterion for text summaries, and the summaries generated by the KGIT model can contain more key information and are more accurate and readable when compared with the mainstream summary generation models on the NLPCC2017 Chinese news summary dataset.

Citation Download Citation

Wenming Huang, Xianghui Bu, Yannan Xiao, Yayuan Wen, and Zhenrong Deng "Research on Chinese summary generation based on pointer key information", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 124512J (20 October 2022); https://doi.org/10.1117/12.2656552

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KEYWORDS

Data modeling

Transformers

Performance modeling

Computer programming

Information fusion

Systems modeling

Feature extraction

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