Shared Feature-Based Joint Entity and Relation Extraction Network

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Artificial Intelligence | 更新时间：2025-09-30

- Shared Feature-Based Joint Entity and Relation Extraction Network
- “In the field of information extraction, the SJERE network effectively improves the performance of joint entity relationship extraction by sharing feature modules.”
- Software Guide Vol. 24, Issue 9, Pages: 41-47(2025)
- 作者机构：
  
  1.齐鲁工业大学（山东省科学院）山东省计算中心（国家超级计算济南中心）算力互联网与信息安全教育部重点实验室
  2.齐鲁工业大学（山东省科学院）计算机科学与技术学部大数据应用技术山东省工程研究中心
  3.山东省工业网络和信息系统安全重点实验室山东省基础科学研究中心（计算机科学），山东济南 250353
- 作者简介：
- 基金信息：
- DOI：10.11907/rjdk.241626
  CLC： TP391
- Received：22 July 2024，
  
  Published：15 September 2025
- 稿件说明：
移动端阅览
郝增昊,赵晶.基于共享特征的联合实体关系抽取网络[J].软件导刊,2025,24(09):41-47.

HAO Zenghao,ZHAO Jing.Shared Feature-Based Joint Entity and Relation Extraction Network[J].Software Guide,2025,24(09):41-47.
郝增昊,赵晶.基于共享特征的联合实体关系抽取网络[J].软件导刊,2025,24(09):41-47. DOI： 10.11907/rjdk.241626.

HAO Zenghao,ZHAO Jing.Shared Feature-Based Joint Entity and Relation Extraction Network[J].Software Guide,2025,24(09):41-47. DOI： 10.11907/rjdk.241626.

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