计算机应用研究2024，Vol.41Issue(10)：2893-2899,7.DOI:10.19734/j.issn.1001-3695.2024.02.0022
大语言模型领域意图的精准性增强方法
Intention recognition accuracy enhancing method for large language model
摘要
Abstract
Large language models(such as GPT)exhibit instability and inauthenticity in professional domain Q&A applica-tions.To address this issue,this paper proposed a method to enhance intent recognition by domain knowledge(EIRDK)for large language models.The method involved three specific strategies:a)scoring and filtering the GPT output using a domain knowledge base,b)training the domain knowledge word vector mode to optimize prompt,c)utilizing feedback from GPT to im-prove the coherence between the domain word vector model and the GPT model.Experimental analysis demonstrates that,com-pared to the standard GPT model,the new method achieves a 25％improvement in intent understanding accuracy on the pri-vate dataset and a 12％increase on the CMID dataset.The results validate the effectiveness of the EIRDK method.关键词
大语言模型知识问答/意图精准性增强/领域知识集成/GPT反馈学习Key words
knowledge Q&A with large language models/intent recognition accuracy enhancement/domain knowledge inte-gration/feedback learning from GPT分类
信息技术与安全科学引用本文复制引用
任元凯,谢振平..大语言模型领域意图的精准性增强方法[J].计算机应用研究,2024,41(10):2893-2899,7.基金项目
国家自然科学基金资助项目(62272201) （62272201）
