Ribeiro De Aquino A., Alvares L. O., Renso C., Bogorny V.
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.
Source: Semantic trajectories, Trajectory outlier, Database Applications, pp. 115–126, San Paolo, Brasile, 24-27 November 2013
@inproceedings{oai:it.cnr:prodotti:280396, title = {Towards semantic trajectory outlier detection}, author = {Ribeiro De Aquino A. and Alvares L. O. and Renso C. and Bogorny V.}, booktitle = {Semantic trajectories, Trajectory outlier, Database Applications, pp. 115–126, San Paolo, Brasile, 24-27 November 2013}, year = {2013} }