Novel method for the prediction of mobile location based on temporal-spatial behavioral patterns

The problem of predicting next user location is one of the most interesting and important mobile data mining tasks. Potential applications of the ability to predict the user´s moves range from improving the relevance of location-based recommendations and mobile advertising to network traffic planning and promotion of coordination for disaster relief. In this research, the problem solution is proposed based on the analysis of spatial-temporal trajectories with the help of several classifying algorithms. The algorithm is tested using real data collected from the mobile phones of several non-related users over periods of time varying from a few weeks to two years. The simulation results show that the next user locations can be predicted with a high accuracy rate.