Indoor Location Prediction Method for Shopping Malls Based on Location Sequence Similarity
文献类型：期刊论文
| 作者 | Wang, Peixiao1; Wu, Sheng1; Zhang, Hengcai2,3; Lu, Feng2,3
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| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 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. |
| WOS关键词 | PEOPLE MOVEMENT ; ALGORITHM |
| 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研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000502272600051 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Development Program of China ; Digital Fujian Program |
| 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. |
入库方式： OAI收割
来源：地理科学与资源研究所
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