GRAPHRULES

"GraphRules: Rule Discovery, Exploration and Visualization of Collaborative Graph Structures"

 Coordinatore IBM RESEARCH GMBH 

 Organization address address: SAEUMERSTRASSE 4
city: RUESCHLIKON
postcode: 8803

contact info
Titolo: Ms.
Nome: Catherine
Cognome: Trachsel
Email: send email
Telefono: -7248292
Fax: -7248581

 Nazionalità Coordinatore Switzerland [CH]
 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-2009-RG
 Funding Scheme MC-IRG
 Anno di inizio 2009
 Periodo (anno-mese-giorno) 2009-12-01   -   2013-11-30

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    IBM RESEARCH GMBH

 Organization address address: SAEUMERSTRASSE 4
city: RUESCHLIKON
postcode: 8803

contact info
Titolo: Ms.
Nome: Catherine
Cognome: Trachsel
Email: send email
Telefono: -7248292
Fax: -7248581

CH (RUESCHLIKON) coordinator 100˙000.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

offer    sources    graph    tagging    extraction    entities    web    clustering   

 Obiettivo del progetto (Objective)

'In this proposal we will offer a unified view of graph mining systems and recommender systems. We propose a system that monitors the time evolution of graph entities (such as customer-product graphs) and allows for a broad set of knowledge extraction operators. The proposed system will feature advanced collaborative tagging techniques, which we call 'auto-tagging' that aim at automating information extraction about the monitored graph entities from various web sources, such as RSS feeds, blog posts and news events. The system will offer several exhiting innovations such as:

- Incorporation of Ontologies and hierarchies on top of the graph structure - Automatic expansion of entity information from diverse web sources - Interactive Exploration of the graph space - Knowledge extraction algorithms, including clustering and bi-clustering, recommendations, anomaly detection and prediction.'

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