Indoor Location Prediction Method for Shopping Malls Based on Location Sequence Similarity

doi:10.3390/ijgi8110517

	Indoor Location Prediction Method for Shopping Malls Based on Location Sequence Similarity
	Wang, Peixiao 1; Wu, Sheng 1; Zhang, Hengcai 2,3; Lu, Feng 2,3
刊名	ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
	2019-11-01
卷号	8 期号:11 页码:18
关键词	indoor location prediction sequence similarity similar user clustering indoor movement trajectory
DOI	10.3390/ijgi8110517
通讯作者	Zhang, Hengcai(zhanghc@lreis.ac.cn)
英文摘要	Fast and accurate indoor location prediction plays an important part in indoor location services. This work proposes an indoor location prediction framework named Indoor-WhereNext. First, a novel algorithm, "indoor spatiotemporal density-based spatial clustering of applications with noise" (Indoor-STDBSCAN), is proposed to detect the stay points in an indoor trajectory and convert them into a location sequence. Then, a spatial-semantic similarity (SSS) method for measuring the similarity between location sequences is defined. SSS comprehensively considers the spatial and semantic similarities between location sequences. Finally, a clustering algorithm is used to obtain similarity user groups based on SSS. These groups are used to train different prediction models to achieve improved results. Extensive experiments were conducted using real indoor Wi-Fi positioning datasets collected in a shopping mall. The results show that the Indoor-WhereNext model markedly outperforms the three existing baseline methods in terms of prediction accuracy and precision.
资助项目	National Natural Science Foundation of China[41771436] ; National Natural Science Foundation of China[41701521] ; National Key Research and Development Program of China[2016YFB0502104] ; National Key Research and Development Program of China[2017YFB0503500] ; Digital Fujian Program[2016-23]
WOS关键词	PEOPLE MOVEMENT ; ALGORITHM
WOS研究方向	Physical Geography ; Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000502272600051
资助机构	National Natural Science Foundation of China ; National Key Research and Development Program of China ; Digital Fujian Program
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/130820]
专题	中国科学院地理科学与资源研究所
通讯作者	Zhang, Hengcai
作者单位	1.Fuzhou Univ, Acad Digital China, Fuzhou 350002, Fujian, Peoples R China 2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, IGSNRR, Beijing 100101, Peoples R China 3.Fujian Collaborat Innovat Ctr Big Data Applicat G, Fuzhou 350002, Fujian, Peoples R China
推荐引用方式 GB/T 7714	Wang, Peixiao,Wu, Sheng,Zhang, Hengcai,et al. Indoor Location Prediction Method for Shopping Malls Based on Location Sequence Similarity[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2019,8(11):18.
APA	Wang, Peixiao,Wu, Sheng,Zhang, Hengcai,&Lu, Feng.(2019).Indoor Location Prediction Method for Shopping Malls Based on Location Sequence Similarity.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,8(11),18.
MLA	Wang, Peixiao,et al."Indoor Location Prediction Method for Shopping Malls Based on Location Sequence Similarity".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 8.11(2019):18.