摘要
本文提出了一种基于自然语言处理(NLP)和知识图谱技术的整改问题关联分析方法。构建整改问题标签体系和知识图谱,应用多维关联分析算法,采用模型推理分析。测试结果验证了本文方法能够准确分析整改问题的特征标签和相似度比例,为提升整改监督质效提供了技术支持。
This paper proposes a method for analyzing the correlation of rectification issues based on Natural Language Processing(NLP)and knowledge graph technology.It constructs a tag system and knowledge graph for rectification issues,applies a multi-dimensional correlation analysis algorithm,and utilizes model reasoning analysis.The test results verify that the method proposed in this paper can accurately analyze the feature tags and similarity ratios of rectification issues,providing technical support for improving the quality and efficiency of rectification supervision.
作者
蒋妍
古健
陈卓
莫为
JIANG Yan;GU Jian;CHEN Zhuo;MO Wei(Chongqing Tobacco Industry Co.,Ltd.,Chongqing 400000)
出处
《软件》
2025年第9期156-158,共3页
Software
关键词
知识图谱
关联性分析
多标签分类
knowledge graph
correlation analysis
multi-label classification
