Chinese named entity recognition method based on multiscale feature fusion Online publication date: Tue, 30-Apr-2024
by Xiaoguang Jiang
International Journal of Biometrics (IJBM), Vol. 16, No. 3/4, 2024
Abstract: In response to the problems of low recognition accuracy and poor recognition efficiency in traditional methods, the paper proposes a Chinese named entity recognition method based on multiscale feature fusion. Firstly, the similarity between each word is calculated using the literal similarity algorithm to obtain synonyms of Chinese named entities. Then, the Chinese named entity features are obtained, including character features, character shape features, binary character features, and word similarity features, through multiscale feature fusion to obtain the Chinese named entity feature set. Finally, the target Chinese named entity for recognition is obtained by matching vocabulary, compressing vocabulary vectors, and integrating character vectors, and the CRF is used to implement Chinese named entity recognition. The experimental results show that the recognition time of this method is only 4.0 s, with a precision rate of up to 99.9% and a recall rate of up to 99.2%.
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