Authors:
Selver Softic
1
;
Martin Ebner
1
;
Laurens De Vocht
2
;
Erik Mannens
2
and
Rik Van de Walle
2
Affiliations:
1
Graz University of Technology, Austria
;
2
Ghent University - iMinds, Belgium
Keyword(s):
Research 2.0, Science 2.0,Web 2.0, SemanticWeb, Social Media, Linked Data, Profiling, Twitter, Microblogs, Web Mining.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Internet Technology
;
Knowledge Management
;
Metadata and Metamodeling
;
Ontologies and the Semantic Web
;
Ontology and the Semantic Web
;
Personalized Web Sites and Services
;
Searching and Browsing
;
Sensor Networks
;
Signal Processing
;
Society, e-Business and e-Government
;
Soft Computing
;
Software Agents and Internet Computing
;
User Modeling
;
Web 2.0 and Social Networking Controls
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
;
Web Programming
Abstract:
Based upon findings and results from our recent research (De Vocht et al., 2011) we propose a generic framework concept for researcher profiling with appliance to the areas of ”Science 2.0” and ”Research 2.0”. Intensive growth of users in social networks, such as Twitter generated a vast amount of information. It has been shown in many previous works that social networks users produce valuable content for profiling and recommendations (Reinhardt et al., 2009; Java et al., 2007; De Vocht et al., 2011). Our research focuses on identifying and locating experts for specific research area or topic. In our approach we apply semantic technologies like (RDFb, SPARQLc), common vocabularies (SIOCd, FOAFe, MOATf, Tag Ontologyg) and Linked Datah (GeoNamesi, COLINDAj) (Berners-Lee, 2006; Bizer et al., 2012) .