Evaluating Distance Measures for Trajectories in the Mobile Setting

Nikolaos Larios, Christos Mitatakis, Vana Kalogeraki, Dimitrios Gunopulos
2015 International Conference on Machine Learning  
Mobile devices, such as smartphones allow us to use computationally expensive algorithms and techniques. In this paper, we study algorithms in order to solve the problem of finding the most similar trajectory within a number of trajectories. We built a framework that enables the user to compare a trajectory Q with trajectories that have been generated and stored on mobile devices. The system returns to the user the most similar trajectory based on the algorithm that has been selected. The
more » ... thms for the measurement of the trajectory similarity have been implemented for mobile devices running Android OS. We evaluate our algorithms with real geospatial data.
dblp:conf/icml/LariosMKG15 fatcat:5qdssfvcfvf5rfmle6ytkw7pqy