A New Approach to Measuring the Similarity of Indoor Semantic Trajectories

doi:10.3390/ijgi10020090

	A New Approach to Measuring the Similarity of Indoor Semantic Trajectories
	Zhu, Jin 1,2; Cheng, Dayu 1,3; Zhang, Weiwei 2; Song, Ci 1,4; Chen, Jie 1,4; Pei, Tao 1,4,5
刊名	ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
	2021-02-01
卷号	10 期号:2 页码:19
关键词	indoor trajectory similarity semantic similarity edit distance indoor positioning data indoor walking distance
DOI	10.3390/ijgi10020090
通讯作者	Pei, Tao(peit@lreis.ac.cn)
英文摘要	People spend more than 80% of their time in indoor spaces, such as shopping malls and office buildings. Indoor trajectories collected by indoor positioning devices, such as WiFi and Bluetooth devices, can reflect human movement behaviors in indoor spaces. Insightful indoor movement patterns can be discovered from indoor trajectories using various clustering methods. These methods are based on a measure that reflects the degree of similarity between indoor trajectories. Researchers have proposed many trajectory similarity measures. However, existing trajectory similarity measures ignore the indoor movement constraints imposed by the indoor space and the characteristics of indoor positioning sensors, which leads to an inaccurate measure of indoor trajectory similarity. Additionally, most of these works focus on the spatial and temporal dimensions of trajectories and pay less attention to indoor semantic information. Integrating indoor semantic information such as the indoor point of interest into the indoor trajectory similarity measurement is beneficial to discovering pedestrians having similar intentions. In this paper, we propose an accurate and reasonable indoor trajectory similarity measure called the indoor semantic trajectory similarity measure (ISTSM), which considers the features of indoor trajectories and indoor semantic information simultaneously. The ISTSM is modified from the edit distance that is a measure of the distance between string sequences. The key component of the ISTSM is an indoor navigation graph that is transformed from an indoor floor plan representing the indoor space for computing accurate indoor walking distances. The indoor walking distances and indoor semantic information are fused into the edit distance seamlessly. The ISTSM is evaluated using a synthetic dataset and real dataset for a shopping mall. The experiment with the synthetic dataset reveals that the ISTSM is more accurate and reasonable than three other popular trajectory similarities, namely the longest common subsequence (LCSS), edit distance on real sequence (EDR), and the multidimensional similarity measure (MSM). The case study of a shopping mall shows that the ISTSM effectively reveals customer movement patterns of indoor customers.
资助项目	National Natural Science Foundation of China[41525004] ; National Natural Science Foundation of China[42071436] ; National Natural Science Foundation of China[41701477] ; State Key Laboratory of Resources and Environmental Information System[201816] ; Research Foundation for Talent Introduction of Suzhou University of Science and Technology[331511203]
WOS研究方向	Computer Science ; Physical Geography ; Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000622583300001
资助机构	National Natural Science Foundation of China ; State Key Laboratory of Resources and Environmental Information System ; Research Foundation for Talent Introduction of Suzhou University of Science and Technology
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/160701]
专题	中国科学院地理科学与资源研究所
通讯作者	Pei, Tao
作者单位	1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Suzhou Univ Sci & Technol, Sch Geog Sci & Geomat Engn, Suzhou 215009, Peoples R China 3.Hebei Univ Engn, Sch Min & Geomat, Handan 056038, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100101, Peoples R China 5.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China
推荐引用方式 GB/T 7714	Zhu, Jin,Cheng, Dayu,Zhang, Weiwei,et al. A New Approach to Measuring the Similarity of Indoor Semantic Trajectories[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2021,10(2):19.
APA	Zhu, Jin,Cheng, Dayu,Zhang, Weiwei,Song, Ci,Chen, Jie,&Pei, Tao.(2021).A New Approach to Measuring the Similarity of Indoor Semantic Trajectories.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,10(2),19.
MLA	Zhu, Jin,et al."A New Approach to Measuring the Similarity of Indoor Semantic Trajectories".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 10.2(2021):19.