SEEK
Semantic EnrichmEnt of trajectory Knowledge discovery
| Coordinatore | CONSIGLIO NAZIONALE DELLE RICERCHE
Organization address
address: Piazzale Aldo Moro 7 contact info |
| Nazionalità Coordinatore | Italy [IT] |
| Sito del progetto | http://www.seek-project.eu |
| Totale costo | 365˙400 € |
| EC contributo | 352˙800 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2011-IRSES |
| Funding Scheme | MC-IRSES |
| Anno di inizio | 2012 |
| Periodo (anno-mese-giorno) | 2012-03-01 - 2015-08-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
CONSIGLIO NAZIONALE DELLE RICERCHE
Organization address
address: Piazzale Aldo Moro 7 contact info |
IT (ROMA) | coordinator | 199˙500.00 |
| 2 |
UNIVERSITA CA' FOSCARI VENEZIA
Organization address
address: DORSODURO 3246 contact info |
IT (VENEZIA) | participant | 88˙200.00 |
| 3 |
UNIVERSITY OF PIRAEUS RESEARCH CENTER
Organization address
address: GR. LAMPRAKI 122 contact info |
EL (PIRAEUS) | participant | 65˙100.00 |
Mappa
Word cloud
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Obiettivo del progetto (Objective)
'A flood of data pertinent to moving objects is available today, and will be more in the near future, particularly due to the automated collection of data from personal devices such as mobile phones and other location-aware devices. Such wealth of data, referenced both in space and time, may enable novel classes of applications of high societal and economic impact, provided that the discovery of consumable and concise knowledge out of these raw data is made possible.
The fundamental hypothesis is that it is possible, in principle, to aid citizens in their mobile activities by analysing the traces of their past activities by means of data mining techniques. For instance, behavioural patterns derived from mobile trajectories may allow inducing traffic flow information, capable to help people travelling efficiently, to help public administrations in traffic-related decision making for sustainable mobility and security management.
Behavioral patterns can be extracted through a knowledge discovery process where positioning data collected from mobile devices are first transformed in semantically enriched trajectory data stored in a database. Then, these data are loaded in a data warehouse and analysed with OLAP operations that allow summarization of the trajectories features. Mobility patterns, the most common movements emerging from data, are computed with suitable spatio-temporal data mining algorithms. A further semantic enrichment step is needed to give context-dependent meaning to the discovered patterns.
The goal of the project is to investigate methods to extract meaningful knowledge from large amount of movement data by defining techniques for an advanced semantic-rich knowledge discovery process.'
Introduzione (Teaser)
The mobility patterns that our mobile phone signals emit can be very useful in a number of applications. This requires new research on exploiting the wealth of data from mobile phones.