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Mobility Prediction Based on Machine Learning

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3 Author(s)
Anagnostopoulos, T. ; Dept. of Inf. & Telecommun., Univ. of Athens, Athens, Greece ; Anagnostopoulos, C. ; Hadjiefthymiades, S.

Mobile applications are required to operate in highly dynamic pervasive computing environments of dynamic nature and predict the location of mobile users in order to act proactively. We focus on the location prediction and propose a new model/framework. Our model is used for the classification of the spatial trajectories through the adoption of Machine Learning (ML) techniques. Predicting location is treated as a classification problem through supervised learning. We perform the performance assessment of our model through synthetic and real-world data. We monitor the important metrics of prediction accuracy and training sample size.

Published in:

Mobile Data Management (MDM), 2011 12th IEEE International Conference on  (Volume:2 )

Date of Conference:

6-9 June 2011