KNOWLEDGE ORGANIZATION

Research on the Construction of an Event Recognition Model for Historical Antique Books Based on Text Generation Technology

  • Wang Yanying ,
  • Wang Hao ,
  • Zhu Hui ,
  • Li Xiaomin
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  • 1 School of Information Management, Nanjing University, Nanjing 210023;
    2 Jiangsu Province Key Laboratory of Data Engineering and Knowledge Services (Nanjing University), Nanjing 210093

Received date: 2022-09-02

  Revised date: 2022-12-06

  Online published: 2023-02-24

Abstract

[Purpose/Significance] To address the problem of event recognition for historical antique books, compare the sequence labeling method and the text generation method, explore the performance of the two methods on ancient Chinese and construct a model to automate historical antique events recognition, improve the efficiency of building knowledge maps for historical antique books. [Method/Process] This paper selected Records of the Three Kingdoms as the original corpus, the sequence labeling experiment was conducted to label Records of the Three Kingdoms event dataset with BMES and construct BBCN-SG model, while the text generation experiment was conducted to construct T5-SG model to compare the performance of the two methods. The RoBERTa-SG and NEZHA-SG models were also constructed to launch the comparison experiments of text generation model. Finally, combining the three text generation models, the Stacking-TRN-SG model was constructed by incorporating the idea of Stacking ensemble learning. [Result/Conclusion] In the modeling problem of event recognition for historical antique books, the text generation method performs significantly better than the sequence labeling method. Among three text generation methods, the RoBERTa-SG model has the best comprehensive recognition effect. Stacking ensemble learning greatly improves the recognition effect of the generation model, and the Stacking-TRN-SG model constructed achieves a recall rate of 70.35%, which initially realizes the automatic event recognition of historical antiquities.

Cite this article

Wang Yanying , Wang Hao , Zhu Hui , Li Xiaomin . Research on the Construction of an Event Recognition Model for Historical Antique Books Based on Text Generation Technology[J]. Library and Information Service, 2023 , 67(3) : 119 -130 . DOI: 10.13266/j.issn.0252-3116.2023.03.011

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