The growing availability of mobile devices produces an enor- mous quantity of personal tracks which calls for advanced analysis methods capable of extracting knowledge out of massive trajectories datasets. In this paper we present an experiment on a real world scenario that demonstrates the strong analytical power of massive, raw trajectory data made available as a by-product of telecom services, in unveiling the complexity of urban mobility. The experiment has been made possible by the GeoPKDD system, an integrated plat- form for complex analysis of mobility data. The system com- bines spatio-temporal querying capabilities with data min- ing and semantic technologies, thus providing a full support for the Mobility Knowledge Discovery process.

Advanced knowledge discovery on movement data with the GeoPKDD system

Trasarti R;Giannotti F;Pedreschi D;Nanni M;Renso C
2010

Abstract

The growing availability of mobile devices produces an enor- mous quantity of personal tracks which calls for advanced analysis methods capable of extracting knowledge out of massive trajectories datasets. In this paper we present an experiment on a real world scenario that demonstrates the strong analytical power of massive, raw trajectory data made available as a by-product of telecom services, in unveiling the complexity of urban mobility. The experiment has been made possible by the GeoPKDD system, an integrated plat- form for complex analysis of mobility data. The system com- bines spatio-temporal querying capabilities with data min- ing and semantic technologies, thus providing a full support for the Mobility Knowledge Discovery process.
2010
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-1-60558-947-3
Database Management. Data mining
Mobility
Data Mining
Privacy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/63138
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