Predicting User’s Movement with a Combination of Self-Organizing Map and Markov Model
In the development of location-based services, various location-sensing 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.
KeywordsMarkov Model Ubiquitous Computing Trajectory Model Movement Prediction Bayesian Network Model
Unable to display preview. Download preview PDF.
- 1.Ashbrook, D., Starner, T.: Learning Significant Locations and Predicting User Movement with GPS. In: Proceedings of IEEE Sixth International Symposium on Wearable Computing, Seattle, WA (October 2002)Google Scholar
- 2.Stilp, L.: Carrier and End-User Applications for Wireless Location Systems. In: Proceedings of SPIE, vol. 2602, pp. 119–126 (1996)Google Scholar
- 7.Patterson, D., Liao, L., Fox, D., Kautz, H.: Inferring High-Level Behavior from Low- Level Sensors. In: Proceedings of the Fifth International Conference on Ubiquitous Computing, Seattle, WA, October 2003, pp. 73–89 (2003)Google Scholar
- 8.Sparacino, F.: Sto(ry)chastics: A Bayesian Network Architecture for User Modeling and Computational Storytelling for Interactive Spaces. In: Proceedings of the Fifth International Conference on Ubiquitous Computing, Seattle, WA, October 2003, pp. 54–72 (2003)Google Scholar
- 10.Koskela, T., Varsta, M., Heikkonen, J., Kaski, K.: Temporal Sequence Processing using Recurrent SOM. In: Proceedings of Second International Conference on Knowledge- Based Intelligent Engineering Systems, Adelaide, Australia, April 1998, vol. 1, pp. 290–297 (1998)Google Scholar