2017
Journal article  Open Access

MyWay: location prediction via mobility profiling

Trasarti R, Guidotti R, Monreale A, Giannotti F

Trajectory Prediction  Mobility Data Mining  Database Applications  Data Mining 

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.

Source: INFORMATION SYSTEMS, vol. 64, pp. 350-367



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BibTeX entry
@article{oai:it.cnr:prodotti:358981,
	title = {MyWay: location prediction via mobility profiling},
	author = {Trasarti R and Guidotti R and Monreale A and Giannotti F},
	year = {2017}
}