Robotics & Machine Learning Daily News2024,Issue(Jul.3) :85-86.

Guangdong University of Foreign Studies Details Findings in Intelligent Systems (Chinese Named Entity Recognition Method Based On Multi-feature Fusion and Biaff ine)

广东外国语大学详述智能系统研究成果(基于多特征融合和biafine的中文命名实体识别方法)

Robotics & Machine Learning Daily News2024,Issue(Jul.3) :85-86.

Guangdong University of Foreign Studies Details Findings in Intelligent Systems (Chinese Named Entity Recognition Method Based On Multi-feature Fusion and Biaff ine)

广东外国语大学详述智能系统研究成果(基于多特征融合和biafine的中文命名实体识别方法)

扫码查看

摘要

由一位新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-机器学习-智能系统的最新研究结果已经发表。根据NewsRx记者在广东的新闻报道,研究表明:“中文命名实体识别(CNER)侧重于准确识别非结构化中文文本中预先定义的结构类别,现有的CNER模型大多没有考虑汉字独特的字形和拼音特征。”但这些特征背后隐藏的丰富语义特征对提高语言模型的判断能力有很好的作用。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing - Intelligent Systems have been published. According to news reporting from Guangdong, People’s Republic of China, by NewsRx journalists, research stated, “ Chinese Named Entity Recognition (CNER) focuses on precisely identifying predefi ned structural categories in unstructured Chinese text. Most existing CNER model s do not consider the unique glyph and pinyin features of Chinese characters, bu t the rich semantic features hidden behind these features have a good effect on enhancing the judgment ability of language models.”

Key words

Guangdong/People's Republic of China/A sia/Intelligent Systems/Emerging Technologies/Machine Learning/Named Entity Recognition/Guangdong University of Foreign Studies

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文