This document presents the key algorithms that form the core of the Mobility Pattern Mining module within the PETRA architecture, as presented in D2.2, devoted to deal with GPS and mobile phone (GSM) individual data. The algorithms learn to identify the role or purpose of each trip or location within the history of a user, in terms of activity to be performed, whether it is a systematic trip or location, etc., and exploit such derived information for prediction purposes. This document provides some preliminaries, the rationale of the methods, highlighting the improvement over the state-of-art, and a brief summary of performances.

PETRA - An individual mobility pattern and diary model for smart cities

Nanni M;Trasarti R;Romano V
2016

Abstract

This document presents the key algorithms that form the core of the Mobility Pattern Mining module within the PETRA architecture, as presented in D2.2, devoted to deal with GPS and mobile phone (GSM) individual data. The algorithms learn to identify the role or purpose of each trip or location within the history of a user, in terms of activity to be performed, whether it is a systematic trip or location, etc., and exploit such derived information for prediction purposes. This document provides some preliminaries, the rationale of the methods, highlighting the improvement over the state-of-art, and a brief summary of performances.
2016
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Rapporto intermedio di progetto
Mobility
Database Applications
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/316756
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