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Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

According to the problem that the model in the generative text summarization doesn’t fully understand the semantics of the text and the generated summary lacks key information, this paper proposed a Key-BERT-Pen model that integrated keywords in Chinese abstract generation. The KBPM first used the TextRank method to extract the keywords in the text, and then obtained a more accurate contextual representation through the BERT pre-training model using the extracted keywords and the original text. Finally, it input the obtained word vector into a pointer model with a dual attention mechanism, and the pointer model took vocabularies from the vocabulary or original text to generate the final abstract. Experimental results show that the KBPM can generate text summaries with better readability and higher ROUGE scores. The comparative analysis also verifies that the KBPM effectively solves the problem of the lack of key information in the generated abstract. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Hebei University of Science & Technology is the property of Hebei University of Science & Technology, Journal of Hebei University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)