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| Citation: | Li Shengmiao, Jia Lining, Wang Chengbin, Zhou Liyun, Liu Bangding, Zhu Jinhao, Wang Yueying, Li Nan, 2026. Clustering of Geological Characteristics and Prospecting Significance of Gold Deposits in the Jiangnan Orogen Based on Knowledge Graphs. Earth Science, 51(3): 1040-1056. doi: 10.3799/dqkx.2026.022
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This study aims to deepen the understanding of metallogenic regularities and evaluate the prospecting potential of gold deposits in the Jiangnan Orogen. Focusing on the gold deposits within and adjacent to the Jiangnan Orogen, technologies related to the knowledge graph were introduced. A domain knowledge schema was developed using a top-down approach, and the metallogeny-exploration knowledge graph of gold deposits was constructed by integrating deep learning and Large Language Models (LLM). Community detection and Jaccard similarity evaluation were used to analyze the clustering characteristics of the gold deposits. The knowledge schema contains 28 geological entity types and 10 semantic relationship types. The resulting knowledge graph encompasses 60 representative gold deposits in the region, containing 2 212 geological entities and 5 497 semantic relationships. Community detection successfully extracted key ore-controlling factor combinations and metallogenic regularities, such as "alteration-mineral-strata". Jaccard similarity analysis indicates that the Shuikoushan and Huangjindong gold deposits have high similarities to global large-to-giant deposits, revealing significant prospecting potential in their deep-seated zones and peripheral areas.
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Bai, D. Y., Li, B., Zeng, G. Q., et al., 2025. Tectonic Ore-Controlling Characteristics and Dynamic Mechanism of the Hunan Segment of the Jiangnan Gold Ore Belt. Geotectonica et Metallogenia, Online (in Chinese with English abstract).
|
|
Blondel, V. D., Guillaume, J., Lambiotte, R., et al., 2008. Fast Unfolding of Communities in Large Networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10): P10008. https://iopscience.iop.org/article/10.1088/1742-5468/2008/10/P10008 doi: 10.1088/1742-5468/2008/10/P10008
|
|
Deng, Y. Y., Song, S. C., Fan, J. X., et al., 2024. Paleontology Knowledge Graph for Data-Driven Discovery. Journal of Earth Science, 35(3): 1024-1034. https://doi.org/10.1007/s12583-023-1943-9
|
|
Dong, S. C., Shi, Y. K., Ran, Y. Z., et al., 2024. Biological Classification System Knowledge Graph and Semi-Automatic Construction of Its Invertebrate Fossil Branches. Journal of Earth Science, 35(6): 2119-2128. https://doi.org/10.1007/s12583-023-1941-y
|
|
Enkhsaikhan, M., Liu, W., Holden, E. J., et al., 2021. Auto-Labelling Entities in Low-Resource Text: A Geological Case Study. Knowledge and Information Systems, 63(3): 695-715. https://doi.org/10.1007/s10115-020-01532-6
|
|
Guo, F., Lai, P., Huang, F. M., et al., 2024. Literature Review and Research Progress of Landslide Susceptibility Mapping Based on Knowledge Graph. Earth Science, 49(5): 1584-1606 (in Chinese with English abstract).
|
|
Kong, Y. X., Shi, G. Y., Wu, R. J., et al., 2019. K-Core: Theories and Applications. Physics Reports, 832: 1-32. https://doi.org/10.1016/j.physrep.2019.10.004
|
|
Li, G. Z., Wang, P., Liu, J. J., et al., 2024. Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors. arXiv, 2404.17807.
|
|
Li, J., Huang, X. J., Gao, Y. T., et al., 2022. Distant Supervised Relation Extraction Based on Sentence-Level Attention with Relation Alignment. Artificial Intelligence and Security. Cham: Springer International Publishing: 142-152.
|
|
Li, S., Chen, J. P., Xiang, J., 2018. Prospecting Information Extraction by Text Mining Based on Convolutional Neural Networks: A Case Study of the Lala Copper Deposit, China. IEEE Access, 6: 52286-52297.
|
|
Ma, X. F., 2025. Research on Knowledge Extraction Method of Geological Hazards Based on Large Models (Dissertation). Qinghai Normal University, Xining (in Chinese with English abstract).
|
|
Ma, X. G., Ma, C., Wang, C. B., 2020. A New Structure for Representing and Tracking Version Information in a Deep Time Knowledge Graph. Computers & Geosciences, 145: 104620. https://doi.org/10.1016/j.cageo.2020.104620
|
|
Newman, M. E. J., 2006. Modularity and Community Structure in Networks. Proceedings of the National Academy of Sciences of the United States of America, 103(23): 8577-8582. https://doi.org/10.1073/pnas.0601602103
|
|
Niwattanakul, S., Singthongchai, J., Naenudorn, E., et al., 2013. Using of Jaccard Coefficient for Keywords Similarity. The International Multiconference of Engineers and Computer Scientists, Hong Kong.
|
|
Peng, C. Y., Xia, F., Naseriparsa, M., et al., 2023. Knowledge Graphs: Opportunities and Challenges. Artificial Intelligence Review, 56(11): 13071-13102. https://doi.org/10.1007/s10462-023-10465-9
|
|
Qiu, Q. J., Ma, K., Lü, H. R., et al., 2023a. Construction and Application of a Knowledge Graph for Iron Deposits Using Text Mining Analytics and a Deep Learning Algorithm. Mathematical Geosciences, 55(3): 423-456. https://doi.org/10.1007/s11004-023-10050-4
|
|
Qiu, Q. J., Tian, M., Xie, Z., et al., 2023b. Extracting Named Entity Using Entity Labeling in Geological Text Using Deep Learning Approach. Journal of Earth Science, 34(5): 1406-1417. https://doi.org/10.1007/s12583-022-1789-8
|
|
Qiu, Q. J., Wu, L., Ma, K., et al., 2023. A Knowledge Graph Construction Method for Geohazard Chain for Disaster Emergency Response. Earth Science, 48(5): 1875-1891 (in Chinese with English abstract).
|
|
Qiu, Q. J., Xie, Z., Wu, L., et al., 2020. Dictionary-Based Automated Information Extraction from Geological Documents Using a Deep Learning Algorithm. Earth and Space Science, 7(3): e2019EA000993. https://doi.org/10.1029/2019ea000993
|
|
Tian, M., Ma, K., Wu, Q. R., et al., 2024. Joint Extraction of Entity Relations from Geological Reports Based on a Novel Relation Graph Convolutional Network. Computers & Geosciences, 187: 105571. https://doi.org/10.1016/j.cageo.2024.105571
|
|
Vaswani, A., Shazeer, N., Parmar, N., et al., 2017. Attention is All You Need. Proceedings of the 31st International Conference on Neural Information Processing Systems. Long Beach.
|
|
Wang, B., Wu, L., Xie, Z., et al., 2022. Understanding Geological Reports Based on Knowledge Graphs Using a Deep Learning Approach. Computers & Geosciences, 168: 105229. https://doi.org/10.1016/j.cageo.2022.105229
|
|
Wang, C. B., Li, Y. J., Chen, J. G., 2023. Text Mining and Knowledge Graph Construction from Geoscience Literature Legacy: A Review. In: Ma, X., Mookerjee, M., Hsu, L., et al., eds., Recent Advancement in Geoinformatics and Data Science. Geological Society of America, New York.
|
|
Wang, C. B., Ma, X. G., Chen, J. G., et al., 2018. Information Extraction and Knowledge Graph Construction from Geoscience Literature. Computers & Geosciences, 112: 112-120. https://doi.org/10.1016/j.cageo.2017.12.007
|
|
Wang, J. X., 2024. Intelligent Identification of Prospecting Criteria for Porphyry Copper Deposits Based on Large Language Models (Dissertation). Jilin University, Changchun (in Chinese with English abstract).
|
|
Wei, Z. P., Su, J. L., Wang, Y., et al., 2020. A Novel Cascade Binary Tagging Framework for Relational Triple Extraction. The 58th Annual Meeting of the Association for Computational Linguistics. Online.
|
|
Wu, R. Z., Li, H., Mei, H. B., et al., 2025. A Landslide Monitoring and Early Warning System with Retrieval-Augmented Generation Enhanced by Knowledge Graph. Earth Science, 50(10): 4125-4136 (in Chinese with English abstract).
|
|
Xiao, D., Song, W. G., Yan, Z. F., et al., 2025. Geological Characteristics, Metallogenic Regularity and Metallogenic Model of Gold Deposits in the Xuefeng Arcuate Tectonic Belt of Hunan Province. Geology and Exploration, 61(3): 450-463 (in Chinese with English abstract).
|
|
Yang, X., Sun, L., Liu, M. L., et al., 2025. Knowledge Graph Construction with BERT-BiLSTM-IDCNN-CRF and Graph Algorithms for Metallogenic Pattern Discovery: A Case Study of Pegmatite-Type Lithium Deposits in China. Ore Geology Reviews, 179: 106514. https://doi.org/10.1016/j.oregeorev.2025.106514
|
|
Zhang, L. N., Hou, Z. S., Shen, B. H., et al., 2023a. Paleobiogeographic Knowledge Graph: An Ongoing Work with Fundamental Support for Future Research. Journal of Earth Science, 34(5): 1339-1349. https://doi.org/10.1007/s12583-023-1845-z
|
|
Zhang, L., Hou, M. C., Chen, A. Q., et al., 2023b. Construction of a Fluvial Facies Knowledge Graph and Its Application in Sedimentary Facies Identification. Geoscience Frontiers, 14(2): 101521. https://doi.org/10.1016/j.gsf.2022.101521
|
|
Zhou, C. H., Wang, H., Wang, C. S., et al. 2021. Research on Geoscience Knowledge Graph in the Big Data Era. Scientia Sinica Terrae, 51(7): 1070-1079 (in Chinese with English abstract). doi: 10.1360/SSTe-2020-0337
|
|
Zhou, C. H., Wang, H., Wang, C. S., et al., 2021. Geoscience Knowledge Graph in the Big Data Era. Science China Earth Sciences, 64(7): 1105-1114. https://doi.org/10.1007/s11430-020-9750-4
|
|
Zhou, S. Z., Meng, Y., Jin, B. W., et al., 2024. Grasping the Essentials: Tailoring Large Language Models for Zero-Shot Relation Extraction. arXiv, 2402.11142.
|
|
柏道远, 李彬, 曾广乾, 等, 2025. 江南金矿带湖南段构造控矿特征及动力机制. 大地构造与成矿学, 知网首发.
|
|
郭飞, 赖鹏, 黄发明, 等, 2024. 基于知识图谱的滑坡易发性评价文献综述及研究进展. 地球科学, 49(5): 1584-1606. doi: 10.3799/dqkx.2023.058
|
|
马香菲, 2025. 基于大模型的地质灾害知识抽取方法研究(硕士学位论文). 西宁: 青海师范大学.
|
|
邱芹军, 吴亮, 马凯, 等, 2023. 面向灾害应急响应的地质灾害链知识图谱构建方法. 地球科学, 48(5): 1875-1891.
|
|
王嘉翔, 2024. 基于大语言模型的斑岩型铜矿找矿标志智能识别研究(硕士学位论文). 长春: 吉林大学.
|
|
吴润泽, 李浩, 梅红波, 等, 2025. 基于知识图谱检索增强生成的滑坡监测预警系统. 地球科学, 50(10): 4125-4136. doi: 10.3799/dqkx.2025.127
|
|
肖丹, 宋维国, 严志飞, 等, 2025. 湖南雪峰弧形构造带金矿地质特征、成矿规律与成矿模式. 地质与勘探, 61(3): 450-463.
|
|
周成虎, 王华, 王成善, 等, 2021. 大数据时代的地学知识图谱研究. 中国科学: 地球科学, 51(7): 1070-1079.
|
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