Location Prediction on Trajectory Data: A Review
Location prediction is the key technique in many location based services including route navigation, dining location recommendations, and traffic planning and control, to mention a few. This survey provides a comprehensive overview of location prediction, including basic definitions and concepts, al...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2018-06-01
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| Series: | Big Data Mining and Analytics |
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| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2018.9020010 |
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| _version_ | 1832568962018181120 |
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| author | Ruizhi Wu Guangchun Luo Junming Shao Ling Tian Chengzong Peng |
| author_facet | Ruizhi Wu Guangchun Luo Junming Shao Ling Tian Chengzong Peng |
| author_sort | Ruizhi Wu |
| collection | DOAJ |
| description | Location prediction is the key technique in many location based services including route navigation, dining location recommendations, and traffic planning and control, to mention a few. This survey provides a comprehensive overview of location prediction, including basic definitions and concepts, algorithms, and applications. First, we introduce the types of trajectory data and related basic concepts. Then, we review existing location-prediction methods, ranging from temporal-pattern-based prediction to spatiotemporal-pattern-based prediction. We also discuss and analyze the advantages and disadvantages of these algorithms and briefly summarize current applications of location prediction in diverse fields. Finally, we identify the potential challenges and future research directions in location prediction. |
| format | Article |
| id | doaj-art-19cc7879f894424a94f4b0e5d3250b86 |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2018-06-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-19cc7879f894424a94f4b0e5d3250b862025-02-02T23:47:25ZengTsinghua University PressBig Data Mining and Analytics2096-06542018-06-011210812710.26599/BDMA.2018.9020010Location Prediction on Trajectory Data: A ReviewRuizhi Wu0Guangchun Luo1Junming Shao2Ling Tian3Chengzong Peng4<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>University of Electronic Science and Technology of China</institution>, <city>Chengdu</city> <postal-code>611731</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>University of Electronic Science and Technology of China</institution>, <city>Chengdu</city> <postal-code>611731</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>University of Electronic Science and Technology of China</institution>, <city>Chengdu</city> <postal-code>611731</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>University of Electronic Science and Technology of China</institution>, <city>Chengdu</city> <postal-code>611731</postal-code>, <country>China</country>.<institution content-type="dept">School of Computer Science and Engineering</institution>, <institution>University of Electronic Science and Technology of China</institution>, <city>Chengdu</city> <postal-code>611731</postal-code>, <country>China</country>.Location prediction is the key technique in many location based services including route navigation, dining location recommendations, and traffic planning and control, to mention a few. This survey provides a comprehensive overview of location prediction, including basic definitions and concepts, algorithms, and applications. First, we introduce the types of trajectory data and related basic concepts. Then, we review existing location-prediction methods, ranging from temporal-pattern-based prediction to spatiotemporal-pattern-based prediction. We also discuss and analyze the advantages and disadvantages of these algorithms and briefly summarize current applications of location prediction in diverse fields. Finally, we identify the potential challenges and future research directions in location prediction.https://www.sciopen.com/article/10.26599/BDMA.2018.9020010location predictiontrajectory datadata mining |
| spellingShingle | Ruizhi Wu Guangchun Luo Junming Shao Ling Tian Chengzong Peng Location Prediction on Trajectory Data: A Review Big Data Mining and Analytics location prediction trajectory data data mining |
| title | Location Prediction on Trajectory Data: A Review |
| title_full | Location Prediction on Trajectory Data: A Review |
| title_fullStr | Location Prediction on Trajectory Data: A Review |
| title_full_unstemmed | Location Prediction on Trajectory Data: A Review |
| title_short | Location Prediction on Trajectory Data: A Review |
| title_sort | location prediction on trajectory data a review |
| topic | location prediction trajectory data data mining |
| url | https://www.sciopen.com/article/10.26599/BDMA.2018.9020010 |
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