Conflating point of interest (POI) data: A systematic review of matching methods
文献类型：期刊论文
| 作者 | Sun, Kai1,2; Hu, Yingjie1; Ma, Yue1; Zhou, Ryan Zhanqi1; Zhu, Yuanqiang2,3 |
| 刊名 | COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
 |
| 出版日期 | 2023-07-01 |
| 卷号 | 103页码:14 |
| 关键词 | Point of interest POI POI matching POI conflation Machine learning Urban studies |
| ISSN号 | 0198-9715 |
| DOI | 10.1016/j.compenvurbsys.2023.101977 |
| 通讯作者 | Hu, Yingjie(yhu42@buffalo.edu) ; Zhu, Yuanqiang(zhuyq@igsnrr.ac.cn) |
| 英文摘要 | Point of interest (POI) data provide digital representations of places in the real world, and have been increasingly used to understand human-place interactions, support urban management, and build smart cities. Many POI datasets have been developed, which often have different geographic coverages, attribute focuses, and data quality. From time to time, researchers may need to conflate two or more POI datasets in order to build a better representation of the places in the study areas. While various POI conflation methods have been developed, there lacks a systematic review, and consequently, it is difficult for researchers new to POI conflation to quickly grasp and use these existing methods. This paper fills such a gap. Following the protocol of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), we conduct a systematic review by searching through three bibliographic databases using reproducible syntax to identify related studies. We then focus on a main step of POI conflation, i.e., POI matching, and systematically summarize and categorize the identified methods. Current limitations and future opportunities are discussed afterwards. We hope that this review can provide some guidance for researchers interested in conflating POI datasets for their research. |
| WOS关键词 | VISUALIZATION ; SIGNATURES |
| 资助项目 | National Key R amp; D Program of China[CAS-WX2021SF-0106] ; Informatization Plan of Chinese Academy of Sciences ; [2022YFB3904201] |
| WOS研究方向 | Computer Science ; Engineering ; Environmental Sciences & Ecology ; Geography ; Operations Research & Management Science ; Public Administration |
| 语种 | 英语 |
| WOS记录号 | WOS:001054726900001 |
| 出版者 | ELSEVIER SCI LTD |
| 资助机构 | National Key R amp; D Program of China ; Informatization Plan of Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/196692]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Hu, Yingjie; Zhu, Yuanqiang |
| 作者单位 | 1.Univ Buffalo, Dept Geog, GeoAI Lab, Buffalo, NY 14203 USA 2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China 3.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Sun, Kai,Hu, Yingjie,Ma, Yue,et al. Conflating point of interest (POI) data: A systematic review of matching methods[J]. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS,2023,103:14. |
| APA | Sun, Kai,Hu, Yingjie,Ma, Yue,Zhou, Ryan Zhanqi,&Zhu, Yuanqiang.(2023).Conflating point of interest (POI) data: A systematic review of matching methods.COMPUTERS ENVIRONMENT AND URBAN SYSTEMS,103,14. |
| MLA | Sun, Kai,et al."Conflating point of interest (POI) data: A systematic review of matching methods".COMPUTERS ENVIRONMENT AND URBAN SYSTEMS 103(2023):14. |
入库方式： OAI收割
来源：地理科学与资源研究所
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