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ISTI

where YOu Go is where you Are

Acronym: 
YOGA
Start Date: 
1 July 2012
End date: 
30 June, 2014
Founded by: 
Bilateral collaboration CNR-CNPQ
Research Line: 

Behavioral patterns can be extracted from the traces of past human activities through a semantic- enriched knowledge discovery process.
Here, positioning data are first transformed in semantically enriched trajectory data stored in a database. Then, mobility patterns, the most common movements emerging from data, are computed with data mining algorithms. A further semantic enrichment step is needed to give context-dependent meaning to the discovered patterns. New challenging research topics result from this work.

Paolo Cintia

Born in Marsciano(PG), 4th november 1983.

Actually i'm a Phd Student in Computer Science at the graduate studies school "G. Galilei" of Pisa. My main interests in researching are about mobility mining and location prediction.

In 2006 I got my bachelor degree in Computer Science at university of Perugia, with thesis on "Parallels and distributed algorithms for resolution of propagation equations".

In 2009 I got my master degree in Computer Science at university of Pisa, with thesis on "Map matching of gsm tracks with data mining technique"

Publications

Business Intelligence applied on Coop Data

Acronym: 
BI-COOP

is an industrial R&D project funded by Unicoop, one of largest italian retail companies. KDDLab created a very large sales data warehouse, equipped with advanced BI solutions for strategic marketing and customer care based on data mining predictive analytics.

Osservatorio Turismo Pisa

Acronym: 
OTP
Start Date: 
1 September 2011
End date: 
1 August, 2012
Research Line: 

The aim of the project is to study the touristic flows in Pisa thanks to the analysis and the integration of different types of data: GPS traces, GSM call, Flickr photos and social and demographical data.

DataSIM

Acronym: 
DataSIM
Start Date: 
1 October 2011
End date: 
1 September, 2014

DATSIM aims at providing an entirely new and highly detailed spatial-temporal microsimulation methodology for human mobility, grounded on massive amounts of Big data of various types and from various sources, e.g. GPS, mobile phones and social networking sites, with the goal to forecast the nation-wide consequences of a massive switch to electric vehicles, given the intertwined nature of mobility and power distribution networks.

Gabrielli Lorenzo

Publications

Gozzi

Publications

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