Abstract
Some recent advancements in the area of Mobility Data Analysis are discussed, a field in which data mining and machine learning methods are applied to infer descriptive patterns and predictive models from digital traces of (human) movement.
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References
PETRA: Personal transport advisor: an integrated platform of mobility patterns for Smart Cities to enable demand-adaptive transportation systems. http://petraproject.eu/.
Andrienko, G., N. Andrienko, S. Rinzivillo, M. Nanni, D. Pedreschi, and F. Giannotti. 2009. Interactive Visual Clustering of Large Collections of Trajectories. VAST: Symposium on Visual Analytics Science and Technology.
Giannotti, Fosca, Mirco Nanni, Dino Pedreschi, Fabio Pinelli, Chiara Renso, Salvatore Rinzivillo, and Roberto Trasarti. 2011. Unveiling the complexity of human mobility by querying and mining massive trajectory data. The VLDB Journal 20 (5): 695–719.
Guidotti, R., M. Nanni, S. Rinzivillo, D. Pedreschi, and F. Giannotti. 2016. Never drive alone: boosting carpooling with network analysis. Information Systems.
Rinzivillo, Salvatore, Lorenzo Gabrielli, Mirco Nanni, Luca Pappalardo, Dino Pedreschi, and Fosca Giannotti. 2014. The purpose of motion: learning activities from individual mobility networks. In International Conference on Data Science and Advanced Analytics, DSAA 2014, Shanghai, China, October 30 - November 1, 2014.
Trasarti, R., R. Guidotti, A. Monreale, and F. Giannotti. 2015. Myway: Location prediction via mobility profiling. Information Systems.
Trasarti, Roberto, Fabio Pinelli, Mirco Nanni, and Fosca Giannotti. 2011. Mining mobility user profiles for car pooling. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD’11, 1190–1198. New York, NY, USA, ACM.
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Nanni, M. (2018). Advancements in Mobility Data Analysis. In: Leuzzi, F., Ferilli, S. (eds) Traffic Mining Applied to Police Activities. TRAP 2017. Advances in Intelligent Systems and Computing, vol 728. Springer, Cham. https://doi.org/10.1007/978-3-319-75608-0_2
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DOI: https://doi.org/10.1007/978-3-319-75608-0_2
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