goal and path prediction based on user's moving path data
User adaptive services are important features in many applications. To provide such services, techniques with various kinds of data are being used. In this paper, we propose a method to analyze a user's past moving paths to predict the goal position and the path to the goal by observing the user's current moving path. We developed a spatiotemporal similarity measure between paths. We chose a past path that was most similar to the current path using the similarity measure. Based on the chosen path, the user's spatiotemporal position was estimated. We performed experiments to confirm this method as useful and effective
path selection location based service user's location prediction