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AUTONOMICS
2007
ACM

Adaptive learning of semantic locations and routes

9 years 6 months ago
Adaptive learning of semantic locations and routes
Abstract. Adaptation of devices and applications based on contextual information has a great potential to enhance usability and mitigate the increasing complexity of mobile devices. An important topic in context-aware computing is to learn semantic locations and routes of mobile device users. Several batch methods have been proposed to learn these locations. However, such offline methods have very limited usefulness in practice. This paper describes an online adaptive approach to learn user's semantic locations. The proposed method models user's GPS data as a mixture of Gaussians, which is updated by an online estimation. The learned Gaussian mixture is then evaluated to determine which components most likely correspond to the important locations based on a priori probabilities. With learned semantic locations, we also propose a minimax criterion to discover user's frequent transportation routes, which are modeled as sequences of GPS data. Finally, we describe an applica...
Keshu Zhang, Haifeng Li, Kari Torkkola, Mike Gardn
Added 12 Aug 2010
Updated 12 Aug 2010
Type Conference
Year 2007
Where AUTONOMICS
Authors Keshu Zhang, Haifeng Li, Kari Torkkola, Mike Gardner
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