IGSNRR OpenIR
A Knowledge-Based Filtering Method for Open Relations among Geo-Entities
Yu, Li1,2; Qiu, Peiyuan2; Gao, Jialiang2,3; Lu, Feng2,3,4,5
2019-02-01
Source PublicationISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
ISSN2220-9964
Volume8Issue:2Pages:14
Corresponding AuthorLu, Feng(luf@lreis.ac.cn)
AbstractKnowledge 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.
Keywordgeographical knowledge service knowledge graphs open relation extraction confidence assessment
DOI10.3390/ijgi8020059
Indexed BySCI
Language英语
Funding ProjectNational 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
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program ; State Key Laboratory of Resources and Environmental Information System
WOS Research AreaPhysical Geography ; Remote Sensing
WOS SubjectGeography, Physical ; Remote Sensing
WOS IDWOS:000460762100008
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/49158
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLu, Feng
Affiliation1.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
Recommended Citation
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.
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