Progress and Challenges on Entity Alignment of Geographic Knowledge Bases
文献类型：期刊论文
| 作者 | Sun, Kai1,3,4; Zhu, Yunqiang2,3,4; Song, Jia2,3,4 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2019-02-01 |
| 卷号 | 8期号:2页码:25 |
| 关键词 | geographic knowledge bases entity alignment similarity metrics similarity combination knowledge conflation knowledge integration |
| ISSN号 | 2220-9964 |
| DOI | 10.3390/ijgi8020077 |
| 通讯作者 | Song, Jia(songj@igsnrr.ac.cn) |
| 英文摘要 | Geographic knowledge bases (GKBs) with multiple sources and forms are of obvious heterogeneity, which hinders the integration of geographic knowledge. Entity alignment provides an effective way to find correspondences of entities by measuring the multidimensional similarity between entities from different GKBs, thereby overcoming the semantic gap. Thus, many efforts have been made in this field. This paper initially proposes basic definitions and a general framework for the entity alignment of GKBs. Specifically, the state-of-the-art of algorithms of entity alignment of GKBs is reviewed from the three aspects of similarity metrics, similarity combination, and alignment judgement; the evaluation procedure of alignment results is also summarized. On this basis, eight challenges for future studies are identified. There is a lack of methods to assess the qualities of GKBs. The alignment process should be improved by determining the best composition of heterogeneous features, optimizing alignment algorithms, and incorporating background knowledge. Furthermore, a unified infrastructure, techniques for aligning large-scale GKBs, and deep learning-based alignment techniques should be developed. Meanwhile, the generation of benchmark datasets for the entity alignment of GKBs and the applications of this field need to be investigated. The progress of this field will be accelerated by addressing these challenges. |
| WOS关键词 | SEMANTIC SIMILARITY ; DATA SETS ; ONTOLOGY ; INFORMATION ; WEB ; INTEGRATION ; QUALITY ; LINKEDGEODATA ; CONFLATION ; ALGORITHM |
| 资助项目 | National Natural Science Foundation of China[41631177] ; National Natural Science Foundation of China[41771430] ; National Special Program on Basic Works for Science and Technology of China[2013FY110900] |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000460762100026 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China ; National Special Program on Basic Works for Science and Technology of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/49231]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Song, Jia |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China 3.State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Sun, Kai,Zhu, Yunqiang,Song, Jia. Progress and Challenges on Entity Alignment of Geographic Knowledge Bases[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2019,8(2):25. |
| APA | Sun, Kai,Zhu, Yunqiang,&Song, Jia.(2019).Progress and Challenges on Entity Alignment of Geographic Knowledge Bases.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,8(2),25. |
| MLA | Sun, Kai,et al."Progress and Challenges on Entity Alignment of Geographic Knowledge Bases".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 8.2(2019):25. |
入库方式： OAI收割
来源：地理科学与资源研究所
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