Title: Chinese named entity recognition method based on multiscale feature fusion

Authors: Xiaoguang Jiang

Addresses: Department of Culture and Arts, Yongcheng Vocational College, Yongcheng, 476600, China

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%.

Keywords: multiscale feature fusion; similarity; CRF; literal similarity algorithm.

DOI: 10.1504/IJBM.2024.138233

International Journal of Biometrics, 2024 Vol.16 No.3/4, pp.337 - 349

Received: 09 Jun 2023
Accepted: 29 Aug 2023
Published online: 30 Apr 2024 *

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