Exploring Real Mobility Data with M-Atlas
| Autor: | Salvatore Rinzivillo, Dino Pedreschi, Fosca Giannotti, Roberto Trasarti, Fabio Pinelli, Anna Monreale, Chiara Renso, Mirco Nanni |
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| Rok vydání: | 2010 |
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| Zdroj: | Machine Learning and Knowledge Discovery in Databases ISBN: 9783642159381 ECML/PKDD (3) ECML PKDD 2010-Machine Learning and Knowledge Discovery in Databases. European Conference, pp. 624–627, Barcelona, Spain, 20-24 September 2010 info:cnr-pdr/source/autori:Trasarti R.; Rinzivillo S.; Pinelli F.; Nanni M.; Monreale A.; Renso C.; Pedreschi D.; Giannotti F./congresso_nome:ECML PKDD 2010-Machine Learning and Knowledge Discovery in Databases. European Conference/congresso_luogo:Barcelona, Spain/congresso_data:20-24 September 2010/anno:2010/pagina_da:624/pagina_a:627/intervallo_pagine:624–627 |
| DOI: | 10.1007/978-3-642-15939-8_48 |
| Popis: | Research on moving-object data analysis has been recently fostered by the widespread diffusion of new techniques and systems for monitoring, collecting and storing loca- tion aware data, generated by a wealth of technological infrastructures, such as GPS positioning and wireless networks. These have made available massive repositories of spatio-temporal data recording human mobile activities, that call for suitable analytical methods, capable of enabling the development of innovative, location-aware applica- tions [3]. The M-Atlas is the evolution of the system presented in [5] allows to handle the whole knowledge discovery process from mobility data. The analysis capabilities of M-Atlas system have been applied onto a massive real life GPS dataset, obtained from 17,000 vehicles with on-board GPS receivers under a specific car insurance contract, tracked during one week of ordinary mobile activity in the urban area of the city of Milan; the dataset contains more than 2 million observations leading to a set of more than 200,000 trajectories. |
| Databáze: | OpenAIRE |
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