Scipediacontent: Scipediacontent moved page Draft Content 284318883 to M. et al 2016e

2021-02-11T13:39:39Z

Scipediacontent moved page Draft Content 284318883 to M. et al 2016e

Scipediacontent: Created page with " == 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, devote..."

2021-02-11T13:39:35Z

Created page with " == 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, devote..."

New page

== 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.

== Original document ==

The different versions of the original document can be found in:

* [https://publications.cnr.it/doc/354560 https://publications.cnr.it/doc/354560]

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M. et al 2016e - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 284318883 to M. et al 2016e

Scipediacontent: Created page with " == 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, devote..."