| 成果地质资料知识图谱构建与可视化 |
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| 引用本文： | 王晴,黄进,刘鑫,翟树红,方铮,李剑波.成果地质资料知识图谱构建与可视化[J].计算机系统应用,2022,31(8):140-145. |
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| 作者姓名： | 王晴 黄进 刘鑫 翟树红 方铮 李剑波 |
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| 作者单位： | 西南交通大学 电气工程学院, 成都 611756;四川省自然资源资料馆, 成都 611756;四川省国土科学技术研究院, 成都 611756;西南交通大学 计算机与人工智能学院, 成都 611756 |
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| 基金项目： | 国家自然科学基金(61733015); 高铁联合基金(U1934204); 四川省自然资源科研项目(KYL202106-0099) |
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| 摘 要： | 知识图谱技术在行业领域的运用越来越广,因此研究知识图谱技术在成果地质资料领域中的运用,解决到馆用户的精确查询和可视化问题变得更加重要.本文以成果地质资料为研究对象,利用爬虫技术,爬取成果地质资料中的矿产、地理区域、组织机构等实体信息.结合知识图谱相关技术,设计成果地质资料知识图谱地质实体和关系,经过命名实体识别、关系抽取和属性抽取,构建成果地质资料实体266 787个,关系306 686个.使用Neo4j图形化数据库存储知识图谱来提高地质资料的查询性能,方便到馆用户的查询.该研究可以为知识图谱在成果地质资料上面的应用提供理论支撑.
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| 关 键 词： | 成果地质资料 知识图谱 NLP Neo4j |
| 收稿时间： | 2021/11/17 0:00:00 |
| 修稿时间： | 2021/12/13 0:00:00 |
Construction and Visualization of Knowledge Graph of Geological Report |
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| WANG Qing,HUANG Jin,LIU Xin,ZHAI Shu-Hong,FANG Zheng,LI Jian-Bo.Construction and Visualization of Knowledge Graph of Geological Report[J].Computer Systems& Applications,2022,31(8):140-145. |
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| Authors: | WANG Qing HUANG Jin LIU Xin ZHAI Shu-Hong FANG Zheng LI Jian-Bo |
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| Affiliation: | School of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China;Sichuan Natural Resources Museum, Chengdu 611756, China;Sichuan Academy of Land Science and Technology, Chengdu 611756, China; School of Computer and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, China |
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| Abstract: | Knowledge graph technology is used increasingly widely in industries. Therefore, it is more important to study its application in the field of geological reports to realize accurate queries and visualization for library users. Taking geological reports as the research object, this study uses crawler technology to obtain mineral, geographic area, organization and other entity information in geological reports. With the help of related technologies of knowledge graph, the study designs geological entities and relations for the knowledge graph of geological reports. After named entity recognition, relation extraction and attribute extraction, 266787 geological report entities and 306686 relations are constructed. Knowledge graphs are stored in the Neo4j graph database to improve the performance of geological data query and facilitate the query of library users. This research can provide theoretical support for the application of the knowledge graph to geological reports. |
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| Keywords: | geological report knowledge graph NLP Neo4j |
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