A similarity-based automatic data recommendation approach for geographic models
文献类型：期刊论文
| 作者 | Zhu, Yunqiang1,2,3,11 ; Zhu, A-Xing1,2,9,10,11; Feng, Min4; Song, Jia1,2,3; Zhao, Hongwei5; Yang, Jie1,6; Zhang, Qiuyi7; Sun, Kai1,6; Zhang, Jinqu8; Yao, Ling1,2,3
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| 刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
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| 出版日期 | 2017 |
| 卷号 | 31期号:7页码:1403-1424 |
| 关键词 | Geographic model public data automatic recommendation data similarity data sharing |
| ISSN号 | 1365-8816 |
| DOI | 10.1080/13658816.2017.1300805 |
| 通讯作者 | Song, Jia(songj@igsnrr.ac.cn) |
| 英文摘要 | The complexity of geographic modelling is increasing; hence, preparing data to drive geographic models is becoming a time-consuming and difficult task that may significantly hinder the application of such models. Meanwhile, a huge number of data sets have been shared and have become publicly accessible through the Internet. This study presents a data similarity-based approach to automatically recommend available data sets to fulfil the data requirements of geographic models. Unified description factors are adopted to provide a consistent description of public data sets and input data requirements of geographic models. Five elementary data similarities between them, specifically content, spatial coverage, temporal coverage, spatial precision, and temporal granularity similarities, are calculated. An overall similarity is estimated from aggregating the elementary data similarities. Thereafter, the candidate data for running the models are recommended in the order of overall data similarity. As a case study, the approach has been applied to recommend data from the China National Data Sharing Platform of Earth System Science to drive the population spatialization model (PSM). The approach has successfully recommended the most related data sets to run PSM. The result also suggests that the data recommendation approach can facilitate the intelligent identification of geographic data and the building of links between the open data sets. |
| WOS关键词 | HIERARCHY PROCESS ; DIGITAL EARTH ; WEB SERVICES ; INFORMATION ; ONTOLOGY ; INTEROPERABILITY ; CIRCULATION ; MANAGEMENT ; RETRIEVAL ; SYSTEM |
| 资助项目 | Natural Science Foundation of China[41371381] ; Natural Science Foundation of China[41431177] ; Natural Science Foundation of China[41631177] ; National Special Program on Basic Works for Science and Technology of China[2013FY110900] ; Public and Basic Geological Project of Guizhou Province, China[[2014]23] ; National Basic Research Program of China[2015CB954102] ; Natural Science Research Program of Jiangsu[14KJA170001] ; National Key Technology Innovation Project for Water Pollution Control and Remediation[2013ZX07103006] ; China Scholarship Council |
| WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000400502000007 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 资助机构 | Natural Science Foundation of China ; National Special Program on Basic Works for Science and Technology of China ; Public and Basic Geological Project of Guizhou Province, China ; National Basic Research Program of China ; Natural Science Research Program of Jiangsu ; National Key Technology Innovation Project for Water Pollution Control and Remediation ; China Scholarship Council |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/62693]  |
| 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.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 2.Nanjing Normal Univ, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Jiangsu, Peoples R China 3.Hebei Univ, Collaborat Innovat Ctr Baiyangdian Basin Ecol Pro, Baoding, Peoples R China 4.Univ Maryland, Dept Geog Sci, Global Land Cover Facil, College Pk, MD 20742 USA 5.Chinese Acad Agr Sci, Agr Informat Inst, Dept Cognit Comp, Beijing, Peoples R China 6.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 7.Natl Geomat Ctr China, Dept Standard Qual Management, Beijing, Peoples R China 8.South China Normal Univ, Sch Comp Sci, Guangzhou, Guangdong, Peoples R China 9.Nanjing Normal Univ, Key Lab Virtual Geog Environm, Nanjing, Jiangsu, Peoples R China 10.Nanjing Normal Univ, State Key Lab Cultivat Base Geog Environm Evolut, Nanjing, Jiangsu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhu, Yunqiang,Zhu, A-Xing,Feng, Min,et al. A similarity-based automatic data recommendation approach for geographic models[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2017,31(7):1403-1424. |
| APA | Zhu, Yunqiang.,Zhu, A-Xing.,Feng, Min.,Song, Jia.,Zhao, Hongwei.,...&Yao, Ling.(2017).A similarity-based automatic data recommendation approach for geographic models.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,31(7),1403-1424. |
| MLA | Zhu, Yunqiang,et al."A similarity-based automatic data recommendation approach for geographic models".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 31.7(2017):1403-1424. |
入库方式： OAI收割
来源：地理科学与资源研究所
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