JMUGCS

Jointly Mining User Generated Content Sources

 Coordinatore UNIVERSITY OF IOANNINA 

 Organization address address: "LEOFOROS STAVROS S NIARCHOS, PANEPISTIMIOUPOLI IOANNINON"
city: IOANNINA
postcode: 45110

contact info
Titolo: Prof.
Nome: Evaggelia
Cognome: Pitoura
Email: send email
Telefono: 302651000000

 Nazionalità Coordinatore Greece [EL]
 Totale costo 100˙000 €
 EC contributo 100˙000 €
 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-2012-CIG
 Funding Scheme MC-CIG
 Anno di inizio 2012
 Periodo (anno-mese-giorno) 2012-10-01   -   2016-09-30

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    UNIVERSITY OF IOANNINA

 Organization address address: "LEOFOROS STAVROS S NIARCHOS, PANEPISTIMIOUPOLI IOANNINON"
city: IOANNINA
postcode: 45110

contact info
Titolo: Prof.
Nome: Evaggelia
Cognome: Pitoura
Email: send email
Telefono: 302651000000

EL (IOANNINA) coordinator 100˙000.00

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interact    data    web    sources    content    mining    jointly    settings   

 Obiettivo del progetto (Objective)

'The advent of web 2.0 empowered users to actively interact with the Web instead of passively consuming web content. Today, Web users contribute content to blogs, wiki sites, review portals, and organize themselves into online social networks where they form relationships post their thoughts and activities, and interact with each other. Individuals can now have a “presence” on the web that goes well beyond creating a home page and some documents. This kind of data is a goldmine for scientific research with an unlimited number of practical applications. In this proposed research we are interested in jointly mining user-generated content with other sources of data, in order to enhance our understanding of data, and improve the knowledge extraction process. We consider two settings: jointly mining two different sources of user-generated content, and jointly mining user-generated content with structured data. We propose problems within these two settings, focusing on ranking, and translation of user-generated attributes.'

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