Enhancing semantic accuracy in geographic knowledge graph embeddings through temporal encoding
文献类型：期刊论文
| 作者 | Zhang, Chunju2; Xu, Bing2; Wang, Shu1,3,4; Zhu, Yunqiang1,3,4; Chu, Chaoqun2; Zhou, Kang2 |
| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
 |
| 出版日期 | 2025-09-02 |
| 卷号 | 39期号:9页码:2126-2150 |
| 关键词 | Geographic knowledge graphs (GKG) temporal representation in knowledge graphs logical query in knowledge graphs knowledge graph embedding (KGE) |
| ISSN号 | 1365-8816 |
| DOI | 10.1080/13658816.2025.2542403 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | Geographic knowledge graphs (GKG), central to GeoAI, represent the culmination of knowledge engineering in the era of geographic big data. Knowledge Graph Embedding (KGE) transforms entities and relationships within a knowledge graph into a low-dimensional vector space, effectively capturing their semantic and structural properties. Geographic object knowledge encompasses both intrinsic features and spatiotemporal characteristics, with temporal features indicating the existence or state changes of objects. However, neglecting temporal aspects-such as order, continuity, granularity, and periodicity-during vector calculations can distort the embedding space, reducing the effectiveness of time-sensitive geographic queries, link prediction, and recommendations. This study introduced a temporal feature encoder and designed a fusion mechanism that integrated geographic objects and temporal features. Grounded in logical query tasks, this approach aims to enhance the temporal expressiveness by refining temporal embeddings, thereby improving query accuracy for time-sensitive tasks. A comparative analysis was conducted to evaluate the effects of different baseline models, temporal encoders, and temporal feature weights on the performance of geographic queries. |
| URL标识 | 查看原文 |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001547043300001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/215611]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Wang, Shu |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Geog Informat Sci & Technol, Beijing, Peoples R China; 2.Hefei Univ Technol, Coll Civil Engn, Hefei, Peoples R China; 3.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing, Peoples R China 4.Univ Chinese Acad Sci, Geog Sci & Nat Resources Res, Beijing, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Zhang, Chunju,Xu, Bing,Wang, Shu,et al. Enhancing semantic accuracy in geographic knowledge graph embeddings through temporal encoding[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2025,39(9):2126-2150. |
| APA | Zhang, Chunju,Xu, Bing,Wang, Shu,Zhu, Yunqiang,Chu, Chaoqun,&Zhou, Kang.(2025).Enhancing semantic accuracy in geographic knowledge graph embeddings through temporal encoding.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,39(9),2126-2150. |
| MLA | Zhang, Chunju,et al."Enhancing semantic accuracy in geographic knowledge graph embeddings through temporal encoding".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 39.9(2025):2126-2150. |
入库方式： OAI收割
来源：地理科学与资源研究所
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