Towards semantic trajectory outlier detection

Only a few works in trajectory data mining have focused on outlier detection, and to the best of our knowledge, no works so far have made a deeper analysis to either understand or to give a meaning to the outliers. In this paper we present an algorithm to add meaning to trajectory outliers considering three main possible reasons for a detour: stops outside the standard route, events, and traffic jams in the standard path. We show with experiments on real data that the method correctly finds the different types of outliers.