Chinese long text news summary based on BERTSUM-BART

Haowen Sun; Feng Yao

doi:10.1117/12.2681602

1 June 2023 Chinese long text news summary based on BERTSUM-BART

Haowen Sun, Feng Yao

Proceedings Volume 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023); 127181L (2023) https://doi.org/10.1117/12.2681602
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 2023, Nanjing, China

Abstract

For time-sensitive and large-scale text information such as news, traditional abstract summarization methods may lead to deviation from the subject, distortion and incompleteness of information. To this end, we propose an improved scheme based on automatic text summarization technology, which combines the characteristics of BERTSUM(BERT-based Text Summarization) and BART (Bidirectional and Auto-Regressive Transformers) models. Specifically, we input the same text information into the BERTSUM and BART models respectively, and obtain the key sentence granules of relevant text information through the BERTSUM model and the summary text processed by the BART model, and combine the processing results of the two models into a mixed data Set, and generate a summary through the BART model again to get the final summary result. The effectiveness of the BERTSUM-BART method was verified through experiments based on news long text data. The average recall rate of ROUGE-1, ROUGE-2 and ROUGE-L reached 39.83, 18.05 and 36.46.

Citation Download Citation

Haowen Sun and Feng Yao "Chinese long text news summary based on BERTSUM-BART", Proc. SPIE 12718, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), 127181L (1 June 2023); https://doi.org/10.1117/12.2681602

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