计算机与现代化Issue(9)：8-14,7.DOI:10.3969/j.issn.1006-2475.2024.09.002
基于知识图谱增强大语言模型双碳领域服务
Enhanced Big Language Model Dual Carbon Domain Services Based on Knowledge Graph
摘要
Abstract
With the continuous development of the large language model,it has been widely applied in many fields.Due to the lack of knowledge in the dual carbon field in the big language model,the accuracy of the response results is low if the large lan-guage model is directly applied to the field of double carbon.Therefore,the method of constructing dual carbon knowledge graph as a knowledge base is adopted to enhance the application of large language models in the field of carbon peaking and carbon neu-trality.The LoRA method is used to fine-tune the large language model to improve its ability to extract keywords in the carbon peaking and carbon neutrality fields.A dual carbon knowledge graph is constructed as local knowledge base to provide dual car-bon domain knowledge for the model.The knowledge is used as the context of the problem,allowing the large language model to learn,and a prompt engineering assistance model is designed to generate responses.Finally,the effectiveness of the responses is evaluated.The experimental results show that,compared with the direct use of large language model,the method based on knowl-edge graph to enhance the dual carbon domain service of large language model has a high accuracy of intelligent response results in the field of carbon peaking and carbon neutrality,and provides an effective assistance for the construction of carbon peaking and carbon neutrality.关键词
大语言模型/知识图谱/知识库/LoRA方法/碳达峰碳中和Key words
large language model/knowledge graph/knowledge base/LoRA method/peak carbon dioxide emissions and car-bon neutrality分类
信息技术与安全科学引用本文复制引用
齐俊,曲睿婷,教传铭,周巧妮,郭彦良,覃文军..基于知识图谱增强大语言模型双碳领域服务[J].计算机与现代化,2024,(9):8-14,7.基金项目
国家电网有限公司总部科技项目(5108-202218280A-2-404-XG) （5108-202218280A-2-404-XG）
