@article {821,
	title = {MyWay: Location prediction via mobility profiling},
	journal = {Information Systems},
	volume = {64},
	year = {2017},
	month = {03/2017},
	pages = {350{\textendash}367},
	abstract = {Forecasting the future positions of mobile users is a valuable task allowing us to operate efficiently a myriad of different applications which need this type of information. We propose MyWay, a prediction system which exploits the individual systematic behaviors modeled by mobility profiles to predict human movements. MyWay provides three strategies: the individual strategy uses only the user individual mobility profile, the collective strategy takes advantage of all users individual systematic behaviors, and the hybrid strategy that is a combination of the previous two. A key point is that MyWay only requires the sharing of individual mobility profiles, a concise representation of the user׳s movements, instead of raw trajectory data revealing the detailed movement of the users. We evaluate the prediction performances of our proposal by a deep experimentation on large real-world data. The results highlight that the synergy between the individual and collective knowledge is the key for a better prediction and allow the system to outperform the state-of-art methods.},
	author = {Roberto Trasarti and Riccardo Guidotti and Anna Monreale and Fosca Giannotti}
}
