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Learning transportation mode from raw gps data for geographic applications on the web

10 years 3 months ago
Learning transportation mode from raw gps data for geographic applications on the web
Geographic information has spawned many novel Web applications where global positioning system (GPS) plays important roles in bridging the applications and end users. Learning knowledge from users' raw GPS data can provide rich context information for both geographic and mobile applications. However, so far, raw GPS data are still used directly without much understanding. In this paper, an approach based on supervised learning is proposed to automatically infer transportation mode from raw GPS data. The transportation mode, such as walking, driving, etc., implied in a user's GPS data can provide us valuable knowledge to understand the user. It also enables context-aware computing based on user's present transportation mode and design of an innovative user interface for Web users. Our approach consists of three parts: a change pointbased segmentation method, an inference model and a postprocessing algorithm based on conditional probability. The change point-based segment...
Yu Zheng, Like Liu, Longhao Wang, Xing Xie
Added 21 Nov 2009
Updated 21 Nov 2009
Type Conference
Year 2008
Where WWW
Authors Yu Zheng, Like Liu, Longhao Wang, Xing Xie
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