In this paper we propose a map matching method to overcoming the limitations of standard best-match reconstruction strategies. We use a more flex- ible approach which consider the k-optimal alternative paths to reconstruct the trajectories from the GPS raw data. The preliminary results, obtained on a real dataset of car users in Milan area, suggest that our method leads to beneficial effects on the successive analysis to be performed such as KNN and clustering.

Querying and mining trajectories with gaps: a multi-path reconstruction approach (Extended Abstract)

Nanni M;Trasarti R
2010

Abstract

In this paper we propose a map matching method to overcoming the limitations of standard best-match reconstruction strategies. We use a more flex- ible approach which consider the k-optimal alternative paths to reconstruct the trajectories from the GPS raw data. The preliminary results, obtained on a real dataset of car users in Milan area, suggest that our method leads to beneficial effects on the successive analysis to be performed such as KNN and clustering.
2010
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-88-7488-369-1
Database Applications
62-07
Spatio-temporal data
Map matching
Clustering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/63069
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