01609nas a2200169   4500008004100000245005400041210005300095260001200148300001400160490000700174520108700181100002201268700002301290700001901313700002101332856008601353       2017                        eng d00aMyWay: Location prediction via mobility profiling0 aMyWay Location prediction via mobility profiling  c03/2017  a350–3670 v643 aForecasting 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.1 aTrasarti, Roberto1 aGuidotti, Riccardo1 aMonreale, Anna1 aGiannotti, Fosca  uhttps://kdd.isti.cnr.it/publications/myway-location-prediction-mobility-profiling