y An Automatic Annotation Method for Discovering Semantic Information of Geographical Locations from Location-Based Social Networks

doi:10.3390/ijgi8110487

	y An Automatic Annotation Method for Discovering Semantic Information of Geographical Locations from Location-Based Social Networks
	Zou, Zhiqiang 1,2; He, Xu 1; Zhu, A-Xing 3,4,5,6
刊名	ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
	2019-11-01
卷号	8 期号:11 页码:18
关键词	location-based social networks data mining points of interest Flickr points of interest annotation
DOI	10.3390/ijgi8110487
通讯作者	Zhu, A-Xing(azhu@wisc.edu)
英文摘要	Location-Based Social Networks (LBSNs) contain rich information that can be used to identify and annotate points of interest (POIs). Discovering these POIs and annotating them with this information is not only helpful for understanding the social behavior of users, but it also provides benefits for location recommendations. However, current methods still have some limitations, such as a long annotating time and a low annotating accuracy. In this study, we develop a hybrid method to annotate POIs with meaningful information from LBSNs. The method integrates three patterns: temporal, spatial, and text patterns. Firstly, we present an approach for preprocessing data based on temporal patterns. Secondly, we describe a way to discover POIs through spatial patterns. Thirdly, we build a keyword dictionary for discovering the categories of POIs to be annotated via mining the text patterns. Finally, we integrate these three patterns to label each POI. Taking New York and London as the target areas, we accomplish automatic POI annotation by using Precision, Recall, and F-values to evaluate the effectiveness. The results show that our F-value is 78%, which is superior to that of the baseline method (Falcone's method) at 73% and this suggests that our method is effective in extracting POIs and assigning them categories.
资助项目	National Natural Science Foundation of China[41571389] ; National Natural Science Foundation of China[41871300] ; Key Laboratory of Spatial Data Mining Information Sharing of Ministry of Education, Fuzhou University[2016LSDMIS07] ; National Basic Research Program of China[2015CB954102] ; Natural Science Research Program of Jiangsu[14KJA170001] ; PAPD ; National Key Technology Innovation Project for Water Pollution Control and Remediation[2013ZX07103006] ; Vilas Associate Award from the University of Wisconsin-Madison ; Hammel Faculty Fellow Award from the University of Wisconsin-Madison ; Manasse Chair Professorship from the University of Wisconsin-Madison ; 'One-Thousand Talents' Program of China
WOS研究方向	Physical Geography ; Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000502272600021
资助机构	National Natural Science Foundation of China ; Key Laboratory of Spatial Data Mining Information Sharing of Ministry of Education, Fuzhou University ; National Basic Research Program of China ; Natural Science Research Program of Jiangsu ; PAPD ; National Key Technology Innovation Project for Water Pollution Control and Remediation ; Vilas Associate Award from the University of Wisconsin-Madison ; Hammel Faculty Fellow Award from the University of Wisconsin-Madison ; Manasse Chair Professorship from the University of Wisconsin-Madison ; 'One-Thousand Talents' Program of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/130803]
专题	中国科学院地理科学与资源研究所
通讯作者	Zhu, A-Xing
作者单位	1.Nanjing Univ Posts & Telecommun, Coll Comp, Nanjing 210023, Jiangsu, Peoples R China 2.Jiangsu Key Lab Big Data Secur & Intelligent Proc, Nanjing 210023, Jiangsu, Peoples R China 3.Nanjing Normal Univ, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Sch Geog, Nanjing 210023, Jiangsu, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 5.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA 6.Southern Univ Sci & Technol, Ctr Social Sci, Shenzhen 518055, Guangdong, Peoples R China
推荐引用方式 GB/T 7714	Zou, Zhiqiang,He, Xu,Zhu, A-Xing. y An Automatic Annotation Method for Discovering Semantic Information of Geographical Locations from Location-Based Social Networks[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2019,8(11):18.
APA	Zou, Zhiqiang,He, Xu,&Zhu, A-Xing.(2019).y An Automatic Annotation Method for Discovering Semantic Information of Geographical Locations from Location-Based Social Networks.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,8(11),18.
MLA	Zou, Zhiqiang,et al."y An Automatic Annotation Method for Discovering Semantic Information of Geographical Locations from Location-Based Social Networks".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 8.11(2019):18.