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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 1
107-114

Named entity recognition in motor field based on BERT and multi-window gated CNN

Zhang Zhiyuan1
Sun Shuihua2
Xu Shi'ao2
Xu Fan2
Liu Jianhua2
1. Nanping Electric Power Supply Company, Nanping Fujian 353000, China
2. College of Computer Science & Mathematics, Fujian University of Technology, Fuzhou 350118, China
DOI: 10.19734/j.issn.1001-3695.2022.05.0278

Abstract

Aiming at the problems of difficult and low-accuracy named entity recognition in the motor field, this paper proposed a named entity recognition model in the motor field based on BERT and multi-window gated CNN. Firstly, the model used the BERT pre-training model to generate the character vector sequence of the sentence, and dynamically fine-tuned the character vector according to the context of the text in the motor field to enhance the semantic expression of the character vector; Secondly, it constructed a double-branch feature extraction layer with a global time sequential feature perception unit and a multi-window gated CNN unit to form a multi-level semantic feature representation of sentence; Finally, it used CRF to decode the character sequence to obtain the corresponding label of each character. The results of comparative experiments with multiple models on the small-scale self-built motor field data set show that the named entity recognition performance of the model is better than other models, with macro-F1 values reaching 90.16%, which verifies the effectiveness of entity recognition in motor field.

Foundation Support

福建省自然科学基金资助项目(2019J01061137)
福建工程学院发展基金资助项目(GY-Z20046)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.05.0278
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 1
Section: Algorithm Research & Explore
Pages: 107-114
Serial Number: 1001-3695(2023)01-018-0107-08

Publish History

[2022-08-25] Accepted Paper
[2023-01-05] Printed Article

Cite This Article

张智源, 孙水华, 徐诗傲, 等. 基于BERT和多窗口门控CNN的电机领域命名实体识别 [J]. 计算机应用研究, 2023, 40 (1): 107-114. (Zhang Zhiyuan, Sun Shuihua, Xu Shi'ao, et al. Named entity recognition in motor field based on BERT and multi-window gated CNN [J]. Application Research of Computers, 2023, 40 (1): 107-114. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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