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A u-shaped network-Based Grid Tagging Model for Chinese Named Entity Recognition

Computers, Materials & Continua 2024年第6期79卷 4149-4167页

作者： Yan Xiang Xuedong Zhao Junjun Guo Zhiliang Shi Enbang Chen Xiaobo Zhang Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650504China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and TechnologyKunming650500China Kunming Enersun Technology Co. Ltd.Kunming650217China

Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information *** previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous ***,a unified CNER is often needed in real-world *** studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified ***,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved *** this study,we enhance the character-pair grid representation by incorporating both local and global ***,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation *** devise a u-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character *** approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition *** conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and *** results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.

关键词： Chinese named entity recognition character-pair relation classification grid tagging u-shaped segmentation network

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