Entity Recognition Model for Natural Language Problems

Named entity recognition method can quickly and accurately identify personal names and place names in text information. An improved named entity recognition method based on deep learning is proposed. Firstly, aiming at the problem that the parameters of deep learning affect the recognition results, a multi-strategy slime mold algorithm is proposed to optimize the parameters of deep learning. Then the optimized deep learning algorithm is used for named entity recognition. Finally, through comparative simulation, the proposed method is verified to improve the accuracy of named entity recognition.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/iciscae62304.2024.10761351
Primary Topic
Web Data Mining and Analysis
Type
article
Field-Weighted Citation Impact
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article

Entity Recognition Model for Natural Language Problems

Lai Weiping, Su Zhiyong, Wei Chen, Zhu Yiyuan
Web Data Mining and Analysis
article

Entity Recognition Model for Natural Language Problems

Lai Weiping, Su Zhiyong, Wei Chen, Zhu Yiyuan
article en

Abstract

Named entity recognition method can quickly and accurately identify personal names and place names in text information. An improved named entity recognition method based on deep learning is proposed. Firstly, aiming at the problem that the parameters of deep learning affect the recognition results, a multi-strategy slime mold algorithm is proposed to optimize the parameters of deep learning. Then the optimized deep learning algorithm is used for named entity recognition. Finally, through comparative simulation, the proposed method is verified to improve the accuracy of named entity recognition.

Openalex Percentile: Top 66%
Web Data Mining and Analysis
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Entity Recognition Model for Natural Language Problems — Lai Weiping, Su Zhiyong, et al. · (2024) | TGRS Research Map | TGRS