An adaptive representation model for geoscience knowledge graphs considering complex spatiotemporal features and relationships
文献类型：期刊论文
| 作者 | Zhu, Yunqiang5,6; Sun, Kai6; Wang, Shu6; Zhou, Chenghu6; Lu, Feng6; Lv, Hairong4; Qiu, Qinjun3; Wang, Xinbing2; Qi, Yanmin1,6 |
| 刊名 | SCIENCE CHINA-EARTH SCIENCES
 |
| 出版日期 | 2023-11-01 |
| 卷号 | 66期号:11页码:2563-2578 |
| 关键词 | Geoscience Knowledge graph Representation model Spatiotemporal features Spatiotemporal relationships |
| ISSN号 | 1674-7313 |
| DOI | 10.1007/s11430-022-1169-9 |
| 通讯作者 | Zhu, Yunqiang(zhuyq@igsnrr.ac.cn) ; Sun, Kai(sunk@lreis.ac.cn) |
| 英文摘要 | Geoscience knowledge graph (GKG) can organize various geoscience knowledge into a machine understandable and computable semantic network and is an effective way to organize geoscience knowledge and provide knowledge-related services. As a result, it has gained significant attention and become a frontier in geoscience. Geoscience knowledge is derived from many disciplines and has complex spatiotemporal features and relationships of multiple scales, granularities, and dimensions. Therefore, establishing a GKG representation model conforming to the characteristics of geoscience knowledge is the basis and premise for the construction and application of GKG. However, existing knowledge graph representation models leverage fixed tuples that are limited in fully representing complex spatiotemporal features and relationships. To address this issue, this paper first systematically analyzes the categorization and spatiotemporal features and relationships of geoscience knowledge. On this basis, an adaptive representation model for GKG is proposed by considering the complex spatiotemporal features and relationships. Under the constraint of a unified spatiotemporal ontology, this model adopts different tuples to adaptively represent different types of geoscience knowledge according to their spatiotemporal correlation. This model can efficiently represent geoscience knowledge, thereby avoiding the isolation of the spatiotemporal feature representation and improving the accuracy and efficiency of geoscience knowledge retrieval. It can further enable the alignment, transformation, computation, and reasoning of spatiotemporal information through a spatiotemporal ontology. |
| WOS关键词 | ONTOLOGY ; GEOGRAPHY ; EARTH ; BASE |
| 资助项目 | |
| WOS研究方向 | Geology |
| 语种 | 英语 |
| WOS记录号 | WOS:001088131100001 |
| 出版者 | SCIENCE PRESS |
| 资助机构 | |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/199319]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhu, Yunqiang; Sun, Kai |
| 作者单位 | 1.Univ Nottingham Ningbo China, Sch Comp Sci, Ningbo 315100, Peoples R China 2.Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China 3.China Univ Geosci, Sch Comp Sci, Wuhan 430074, Peoples R China 4.Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China 5.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China 6.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhu, Yunqiang,Sun, Kai,Wang, Shu,et al. An adaptive representation model for geoscience knowledge graphs considering complex spatiotemporal features and relationships[J]. SCIENCE CHINA-EARTH SCIENCES,2023,66(11):2563-2578. |
| APA | Zhu, Yunqiang.,Sun, Kai.,Wang, Shu.,Zhou, Chenghu.,Lu, Feng.,...&Qi, Yanmin.(2023).An adaptive representation model for geoscience knowledge graphs considering complex spatiotemporal features and relationships.SCIENCE CHINA-EARTH SCIENCES,66(11),2563-2578. |
| MLA | Zhu, Yunqiang,et al."An adaptive representation model for geoscience knowledge graphs considering complex spatiotemporal features and relationships".SCIENCE CHINA-EARTH SCIENCES 66.11(2023):2563-2578. |
入库方式： OAI收割
来源：地理科学与资源研究所
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