您当前的位置:
首页 >
文章列表页 >
Educational Named Entity Recognition Integrating Word Information and Self-Attention Mechanism
更新时间:2024-09-25
    • Educational Named Entity Recognition Integrating Word Information and Self-Attention Mechanism

    • 在教育领域,WBBAC模型通过融合词信息与自注意力,显著提升了命名实体识别的精度,有效应对了语料不足的挑战。
    • Software Guide   Vol. 23, Issue 9, Pages: 105-109(2024)
    • DOI:10.11907/rjdk.231921    

      CLC: TP391
    • Published:16 September 2024

      Received:28 August 2023

    移动端阅览

  • ZHENG Shoumin,SHEN Yanguang.Educational Named Entity Recognition Integrating Word Information and Self-Attention Mechanism[J].Software Guide,2024,23(09):105-109. DOI: 10.11907/rjdk.231921.

  •  
  •  

0

Views

0

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Elements Extraction of Alarm Text Based on Multiple Model Fusion
Review of Named Entity Recognition Research
Named Entity Recognition Method for Folk Literature Texts
Named Entity Recognition Method Research Based on the Deep Learning
Research on Lightweight Self-Attention Mechanism as Backbone for Natural Land Cover Segmentation

Related Author

Yu WANG
Yan GONG
Chang-ming LIANG
Lin-yu HUANG
Han YUE
Sheng-ying XU
Ben-qiang WANG
LI Guanfeng

Related Institution

Science and Technology Department,Shanghai Public Security Bureau
DATATOM
School of Information Engineering, Ningxia University
School of Chinese Language and Literature, Yunnan University
Yunnan Key Laboratory of Intelligent Systems and Computing
0