학술논문
A potential approach for mobility prediction using GPS data
Document Type
Conference
Source
2017 Seventh International Conference on Information Science and Technology (ICIST) Information Science and Technology (ICIST), 2017 Seventh International Conference on. :45-50 Apr, 2017
Subject
Language
Abstract
In this paper, we investigate the problem of user movement prediction from historical location data. We create an Android application, namely Movement Predictor, that can help to collect location data from registered users by Global Positioning System (GPS) signals. We analyze different kinds of feature vectors and compare three supervised learning models: Markov model, Support Vector Machine (SVM), and decision tree. The experiments show that SVM model can achieve the highest performance (with an accuracy 92%) in comparison with other approaches.