计算机与数字工程2025，Vol.53Issue(3)：741-746,6.DOI:10.3969/j.issn.1672-9722.2025.03.022
大模型增强下知识库语义扩展智能识别方法
Intelligent Recognition Method for Semantic Extension of Knowledge Base Under Large Model Enhancement
摘要
Abstract
In order to improve the processing capacity and accuracy of the intelligent system,the intelligent recognition meth-od of expanding the knowledge base with large model enhancement is proposed.It divides the continuous text into a series of inde-pendent basic words,calculates the similarity of the words,and selects the key words.For the keywords,the ontology extension al-gorithm is used for semantic expansion.Deep learning approach using self-attention mechanism enables knowledge base semantic extended intelligent recognition by capturing key and contextual information in sequential data.The results show that under the ap-plication of the research method,the intersection ratio is relatively higher,indicating that the overlap between the identification la-bel and the real label is higher,indicating that the method performs better in the identification accuracy.关键词
大模型增强/分词/关键词提取/知识库语义扩展/智能识别Key words
large model enhancement/word segmentation/keyword extraction/semantic extension of knowledge base/in-telligent recognition分类
信息技术与安全科学引用本文复制引用
何剑萍,徐胜超,贺敏伟..大模型增强下知识库语义扩展智能识别方法[J].计算机与数字工程,2025,53(3):741-746,6.基金项目
国家自然科学基金面上项目(编号:61972444) （编号:61972444）
广州华商学院校内科研导师制项目(编号:2023HSDS26)资助. （编号:2023HSDS26）
