An innovative GPS trajectory data based model for geographic recommendation service
Geographic services based on GPS trajectory data, such as location prediction and recommender services, have received increasing attention because of their potential social and commercial benefits. In this study, a Geographic Service Recommender Model (GSRM) is proposed, which loosely comprises thre...
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sg-smu-ink.sis_research-64232020-12-11T06:24:18Z An innovative GPS trajectory data based model for geographic recommendation service ZOU, Zhiqiang YU, Zhe CAO, Kai Geographic services based on GPS trajectory data, such as location prediction and recommender services, have received increasing attention because of their potential social and commercial benefits. In this study, a Geographic Service Recommender Model (GSRM) is proposed, which loosely comprises three essential steps. Firstly, location sequences are obtained through a clustering operation on GPS locations. To improve efficiency, a programming model with a distributed algorithm is employed to accelerate the clustering. Secondly, in order to mine spatial and temporal information from the cluster trajectory, an algorithm (MiningMP) is designed. Last but not least, the next possible location to which the user will travel is predicted. An integrated framework of GSRM could then be constructed and provide the appropriate geographic recommendation service by considering location sequences as well as other related semantic information. Experiments were conducted based on real GPS trajectories from Microsoft Research Asia (182 users within a period of five years). The experimental results clearly demonstrate that our proposed GSRM model is effective and efficient at predicting locations and can provide users with personalized smart recommendation services in the following possible position with excellent performance in scalability, adaptability, and quality of service. 2017-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5420 https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6423&context=sis_research http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University distributed computing location-based services location prediction recommender service trajectory pattern Databases and Information Systems Software Engineering |
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distributed computing location-based services location prediction recommender service trajectory pattern Databases and Information Systems Software Engineering ZOU, Zhiqiang YU, Zhe CAO, Kai An innovative GPS trajectory data based model for geographic recommendation service |
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Geographic services based on GPS trajectory data, such as location prediction and recommender services, have received increasing attention because of their potential social and commercial benefits. In this study, a Geographic Service Recommender Model (GSRM) is proposed, which loosely comprises three essential steps. Firstly, location sequences are obtained through a clustering operation on GPS locations. To improve efficiency, a programming model with a distributed algorithm is employed to accelerate the clustering. Secondly, in order to mine spatial and temporal information from the cluster trajectory, an algorithm (MiningMP) is designed. Last but not least, the next possible location to which the user will travel is predicted. An integrated framework of GSRM could then be constructed and provide the appropriate geographic recommendation service by considering location sequences as well as other related semantic information. Experiments were conducted based on real GPS trajectories from Microsoft Research Asia (182 users within a period of five years). The experimental results clearly demonstrate that our proposed GSRM model is effective and efficient at predicting locations and can provide users with personalized smart recommendation services in the following possible position with excellent performance in scalability, adaptability, and quality of service. |
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ZOU, Zhiqiang YU, Zhe CAO, Kai |
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ZOU, Zhiqiang YU, Zhe CAO, Kai |
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ZOU, Zhiqiang |
title |
An innovative GPS trajectory data based model for geographic recommendation service |
title_short |
An innovative GPS trajectory data based model for geographic recommendation service |
title_full |
An innovative GPS trajectory data based model for geographic recommendation service |
title_fullStr |
An innovative GPS trajectory data based model for geographic recommendation service |
title_full_unstemmed |
An innovative GPS trajectory data based model for geographic recommendation service |
title_sort |
innovative gps trajectory data based model for geographic recommendation service |
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Institutional Knowledge at Singapore Management University |
publishDate |
2017 |
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https://ink.library.smu.edu.sg/sis_research/5420 https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6423&context=sis_research |
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