Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
463871 | Pervasive and Mobile Computing | 2013 | 14 Pages |
Abstract
We present the work that allowed us to win the Next-Place Prediction task of the Nokia Mobile Data Challenge. Using data collected from the smartphones of 80 users, we explore the characteristics of their mobility traces. We then develop three families of predictors, including tailored models and generic algorithms, to predict, based on instantaneous information only, the next place a user will visit. These predictors are enhanced with aging techniques that allow them to adapt quickly to the users’ changes of habit. Finally, we devise various strategies to blend predictors together and take advantage of their diversity, leading to relative improvements of up to 4%.
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Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Vincent Etter, Mohamed Kafsi, Ehsan Kazemi, Matthias Grossglauser, Patrick Thiran,