Predicting User's Movement with a Combination of Self-Organizing Map and Markov Model

In the development of location-based services, various locationsensing techniques and experimental/commercial services have been used. We propose a novel method of predicting the user's future movements in order to develop advanced location-based services. The user’s movement trajectory is modeled using a combination of recurrent self-organizing maps (RSOM) and the Markov model. Future movement is predicted based on past movement trajectories. To verify the proposed method, a GPS dataset was collected on the Yonsei University campus. The results were promising enough to confirm that the application works flexibly even in ambiguous situations.