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Chinese Medical Named Entity Recognition Based on Label Knowledge Enhancement

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Service Science (ICSS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1844))

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Abstract

To solve the problem of text complexity in Chinese medical text named entity task, a model BERT-Label-Span based on label knowledge enhancement had been proposed, which can improve the accuracy of medical information system in Chinese medical named entity recognition task. The model decomposes the problem-text joint coding into two independent coding modules and performs the joint coding based on the BERT pre-training model. Then the semantic fusion module based on the attention mechanism explicitly uses the label knowledge to enhance the representation of medical text. Finally, the span of the named entity is predicted based on the heuristic matching principle. The experiment on the CCKS2019 Chinese medical text dataset shows that the F1 value of the named entity recognition task of the model reaches 85.554, which is higher than the existing main-stream methods and proves the effectiveness of this method.

Supported by National Key R &D Program of China (NO. 2022YFC2503305) and National Science Youth Foundation of Shandong Province of China (NO. ZR2020QF018).

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Authors and Affiliations

  1. University of Science and Technology of China, Hefei, 260026, China

    Shengyu Li, **aonan Si & Biao Wang

  2. Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China

    Shengyu Li, Lei Wang, Wenchang Xu, **aonan Si, Biao Wang, Hanbin Ren & Wenbo Cheng

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  1. Shengyu Li
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  2. Lei Wang
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  3. Wenchang Xu
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  4. **aonan Si
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  5. Biao Wang
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  6. Hanbin Ren
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  7. Wenbo Cheng
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Correspondence to Lei Wang .

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Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Zhongjie Wang

  2. Bei**g University of Posts and Telecommunications, Bei**g, China

    Shangguang Wang

  3. Harbin Institute of Technology, Harbin, China

    Hanchuan Xu

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Li, S. et al. (2023). Chinese Medical Named Entity Recognition Based on Label Knowledge Enhancement. In: Wang, Z., Wang, S., Xu, H. (eds) Service Science. ICSS 2023. Communications in Computer and Information Science, vol 1844. Springer, Singapore. https://doi.org/10.1007/978-981-99-4402-6_21

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  • DOI: https://doi.org/10.1007/978-981-99-4402-6_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-4401-9

  • Online ISBN: 978-981-99-4402-6

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