Mobility Prediction Based on Machine Learning

Anagnostopoulos, T., Anagnostopoulos, C. and Hadjiefthymiades, S. (2011) Mobility Prediction Based on Machine Learning. In: 12th IEEE International Conference on Mobile Data Management (MDM), 2011, Lulea, Sweden, 6-9 Jun 2011, pp. 27-30. (doi: 10.1109/MDM.2011.60)

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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.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Anagnostopoulos, Dr Christos
Authors: Anagnostopoulos, T., Anagnostopoulos, C., and Hadjiefthymiades, S.
Subjects:Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
College/School:College of Science and Engineering > School of Computing Science
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