Personal positioning and location inferences
This FYP about Personal Positioning and Location Inferences is a study on analyzing the location data collected for the discovery of human mobility patterns as well as providing inference and suggestions for various purposes. The technology developed in this project can be applied in many areas to p...
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2011
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sg-ntu-dr.10356-448342023-03-03T20:40:20Z Personal positioning and location inferences Niu, Xudong. Hsu Wen Jing School of Computer Engineering Centre for Advanced Information Systems DRNTU::Engineering::Computer science and engineering This FYP about Personal Positioning and Location Inferences is a study on analyzing the location data collected for the discovery of human mobility patterns as well as providing inference and suggestions for various purposes. The technology developed in this project can be applied in many areas to provide guidance and references for personal or social planning. However, the data to be analyzed could be enormous and in disorder. An efficient yet accurate method is needed to classify the dataset and then discover the mobility pattern of individuals. Human mobility patterns include two fundamental aspects, namely Significant Places (SP) and Representative Trajectories. SPs represent the “hotspots” which the user visits frequently and/or dwell for relatively long period of time, while trajectories reflect how the user traverses among the SPs. By examining the two aspects, certain basic behavior patterns could be found. Bachelor of Engineering (Computer Engineering) 2011-06-06T03:54:22Z 2011-06-06T03:54:22Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/44834 en Nanyang Technological University 65 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering Niu, Xudong. Personal positioning and location inferences |
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This FYP about Personal Positioning and Location Inferences is a study on analyzing the location data collected for the discovery of human mobility patterns as well as providing inference and suggestions for various purposes. The technology developed in this project can be applied in many areas to provide guidance and references for personal or social planning.
However, the data to be analyzed could be enormous and in disorder. An efficient yet accurate method is needed to classify the dataset and then discover the mobility pattern of individuals.
Human mobility patterns include two fundamental aspects, namely Significant Places (SP) and Representative Trajectories. SPs represent the “hotspots” which the user visits frequently and/or dwell for relatively long period of time, while trajectories reflect how the user traverses among the SPs. By examining the two aspects, certain basic behavior patterns could be found. |
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Hsu Wen Jing |
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Hsu Wen Jing Niu, Xudong. |
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Final Year Project |
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Niu, Xudong. |
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Niu, Xudong. |
title |
Personal positioning and location inferences |
title_short |
Personal positioning and location inferences |
title_full |
Personal positioning and location inferences |
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Personal positioning and location inferences |
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Personal positioning and location inferences |
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personal positioning and location inferences |
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2011 |
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http://hdl.handle.net/10356/44834 |
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1759858054182993920 |