A Knowledge-Based Filtering Method for Open Relations among Geo-Entities
文献类型：期刊论文
| 作者 | Yu, Li1,2; Qiu, Peiyuan2; Gao, Jialiang2,3; Lu, Feng2,3,4,5 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2019-02-01 |
| 卷号 | 8期号:2页码:14 |
| 关键词 | geographical knowledge service knowledge graphs open relation extraction confidence assessment |
| ISSN号 | 2220-9964 |
| DOI | 10.3390/ijgi8020059 |
| 通讯作者 | Lu, Feng(luf@lreis.ac.cn) |
| 英文摘要 | Knowledge graphs (KGs) are crucial resources for supporting geographical knowledge services. Given the vast geographical knowledge in web text, extraction of geo-entity relations from web text has become the core technology for construction of geographical KGs; furthermore, it directly affects the quality of geographical knowledge services. However, web text inevitably contains noise and geographical knowledge can be sparsely distributed, both of which greatly restrict the quality of geo-entity relationship extraction. We propose a method for filtering geo-entity relations based on existing knowledge bases (KBs). Accordingly, ontology knowledge, fact knowledge, and synonym knowledge are integrated to generate geo-related knowledge. Then, the extracted geo-entity relationships and the geo-related knowledge are transferred into vectors, and the maximum similarity between vectors is the confidence value of one extracted geo-entity relationship triple. Our method takes full advantage of existing KBs to assess the quality of geographical information in web text, which is helpful to improve the richness and freshness of geographical KGs. Compared with the Stanford OpenIE method, our method decreased the mean square error (MSE) from 0.62 to 0.06 in the confidence interval [0.7, 1], and improved the area under the receiver operating characteristic (ROC) curve (AUC) from 0.51 to 0.89. |
| 资助项目 | National Natural Science Foundation of China[41631177] ; National Natural Science Foundation of China[41801320] ; National Key Research and Development Program[2016YFB0502104] ; State Key Laboratory of Resources and Environmental Information System |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000460762100008 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Development Program ; State Key Laboratory of Resources and Environmental Information System |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/49157]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Lu, Feng |
| 作者单位 | 1.Chinese Acad Sci, Natl Sci Lib, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Fujian Collaborat Innovat Ctr Big Data Applicat G, Fuzhou 350003, Fujian, Peoples R China 5.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Li,Qiu, Peiyuan,Gao, Jialiang,et al. A Knowledge-Based Filtering Method for Open Relations among Geo-Entities[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2019,8(2):14. |
| APA | Yu, Li,Qiu, Peiyuan,Gao, Jialiang,&Lu, Feng.(2019).A Knowledge-Based Filtering Method for Open Relations among Geo-Entities.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,8(2),14. |
| MLA | Yu, Li,et al."A Knowledge-Based Filtering Method for Open Relations among Geo-Entities".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 8.2(2019):14. |
入库方式： OAI收割
来源：地理科学与资源研究所
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