GeoNER:Geological Named Entity Recognition with Enriched Domain Pre-Training Model and Adversarial TrainingOACSTPCD
As important geological data,a geological report contains rich expert and geological knowledge,but the challenge facing current research into geological knowledge extraction and mining is how to render accurate understanding …查看全部>>
MA Kai;HU Xinxin;TIAN Miao;TAN Yongjian;ZHENG Shuai;TAO Liufeng;QIU Qinjun
Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering,China Three Gorges University,Yichang,Hubei 443002,China College of Computer and Information Technology,China Three Gorges University,Yichang,Hubei 443002,ChinaHubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering,China Three Gorges University,Yichang,Hubei 443002,China College of Computer and Information Technology,China Three Gorges University,Yichang,Hubei 443002,ChinaKey Laboratory of Geological Survey and Evaluation of Ministry of Education,China University of Geosciences,Wuhan 430074,ChinaHubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering,China Three Gorges University,Yichang,Hubei 443002,China College of Computer and Information Technology,China Three Gorges University,Yichang,Hubei 443002,ChinaHubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering,China Three Gorges University,Yichang,Hubei 443002,China College of Computer and Information Technology,China Three Gorges University,Yichang,Hubei 443002,ChinaKey Laboratory of Geological Survey and Evaluation of Ministry of Education,China University of Geosciences,Wuhan 430074,China School of Computer Science,China University of Geosciences,Wuhan 430074,China Key Laboratory of Quantitative Resource Evaluation and Information Engineering,Ministry of Natural Resources,China University of Geosciences,Wuhan 430074,ChinaKey Laboratory of Geological Survey and Evaluation of Ministry of Education,China University of Geosciences,Wuhan 430074,China School of Computer Science,China University of Geosciences,Wuhan 430074,China Key Laboratory of Quantitative Resource Evaluation and Information Engineering,Ministry of Natural Resources,China University of Geosciences,Wuhan 430074,China
计算机与自动化
geological named entity recognitiongeological reportadversarial trainingconfrontation trainingglobal pointerpre-training model
《Acta Geologica Sinica(English Edition)》 2024 (5)
P.1404-1417,14
financially supported by the Natural Science Foundation of China(Grant No.42301492)the National Key R&D Program of China(Grant Nos.2022YFF0711600,2022YFF0801201,2022YFF0801200)the Major Special Project of Xinjiang(Grant No.2022A03009-3)the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources(Grant No.KF-2022-07014)the Opening Fund of the Key Laboratory of the Geological Survey and Evaluation of the Ministry of Education(Grant No.GLAB 2023ZR01)the Fundamental Research Funds for the Central Universities。
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