地质科学2026，Vol.61Issue(2)：639-653,15.DOI:10.12017/dzkx.2026.043
联合知识引导与少样本学习的地质图件信息抽取
Geological map information extraction combining knowledge guidance and few-shot learning
摘要
Abstract
Geological maps serve as crucial data sources for reflecting stratigraphy,rock masses,structural features,and other geological information.Extracting domain-specific knowledge from such maps is of significant importance for geological surveys,resource exploration,and mineral prospectivity prediction.However,the inherent complexity of geological structures,the diversity of legend symbols,and the presence of image noise introduce considerable challenges to information extraction.Traditional approaches to geological map information extraction often rely heavily on data quality and availability,while existing large language and vision models also exhibit limitations when directly applied to this domain.To address these challenges,this study focuses on advancing from local extraction to global extraction and proposes a method termed GMIKF(Geological Map Information extraction combining Knowledge guidance and Few-shot learning).The method incorporates external domain knowledge into the GPT-4o model to provide knowledge-guided instruction,while integrating a local visual enhancement mechanism to design visual prompts for geological legends.By combining few-shot prompt learning,the model transitions from legend-level information extraction to comprehensive main-map interpretation.Furthermore,a feedback mechanism is introduced to ensure the accuracy of extraction for each geological map within the dataset.Experimental results demonstrate that,on the geological map dataset constructed in this study,the proposed GMIKF method achieves an extraction accuracy of 93.54％,significantly surpassing the performance of directly applying large models to geological map information extraction(67.42％),yielding an improvement of approximately 26％.These results validate the effectiveness of GMIKF in tackling geological map information extraction tasks.关键词
少样本学习/多模态大模型/提示工程/地质图件/地质知识Key words
Few-shot learning/Multi-modal large model/Prompt engineering/Geological maps/Geological knowledge分类
天文与地球科学引用本文复制引用
马凯,李冰杰,邓钧元,魏东琦,马云霞,鲁谢春,黄泽华,邱芹军,陶留锋..联合知识引导与少样本学习的地质图件信息抽取[J].地质科学,2026,61(2):639-653,15.基金项目
国家自然科学基金项目(编号:42301492)、国家重点研发计划项目(编号:2022YFB3904200,2022YFF0711601)、水电工程智能视觉监测湖北省重点实验室(三峡大学)开放基金项目(编号:2024SDSJ03,2024SDSJ10)、湖北省自然科学基金项目(编号:2025AFB107)和中国地质调查局东天山—北山成矿带区域地质调查项目(编号:DD202402075)资助 （编号:42301492）
