PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Trasarti R., Guidotti R., Monreale A., Giannotti F. MyWay: location prediction via mobility profiling. In: Information Systems, vol. 64 (March 2017) pp. 350 - 367. Elsevier [Online First 19 November 2015], 2017.
 
 
Abstract
(English)
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.
URL: http://www.sciencedirect.com/science/article/pii/S0306437915001945
DOI: http://dx.doi.org/10.1016/j.is.2015.11.002
Subject Trajectory Prediction
Mobility Data Mining
H.2.8 DATABASE MANAGEMENT. Database Applications. Data Mining
68W01 Algorithms


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