Abstract
Use of mobile devices for the personal and corporate purposes is growing rapidly. Context-awareness is an essential feature of the mobile apps. In this paper, we present an approach to predict the next place for a mobile phone by using an online learning method. We represent the model in the form of state-action representation. Each state is a distinct context and behavior of the app is represented in the form of actions applicable at that state. The results show that online learning based approach performs better than two state-of-the-art mobility prediction approaches. Performance is measured in term of accuracy to predict the next location of a mobile host.
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Naveed, M. (2013). Online Learning Based Contextual Model for Mobility Prediction. In: O’Grady, M.J., et al. Evolving Ambient Intelligence. AmI 2013. Communications in Computer and Information Science, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-319-04406-4_32
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DOI: https://doi.org/10.1007/978-3-319-04406-4_32
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04405-7
Online ISBN: 978-3-319-04406-4
eBook Packages: Computer ScienceComputer Science (R0)
