The main objective of this research work is to develop a methodology for ontology profiling scientific research organisations, including:
1.A reliable and valid research subject extraction method developing text mining techniques.
2.An effective method for establishing within-organisation similarities between the ontology items.
3.Adequate clustering methods for representing a research organisation by a set of possibly overlapping or fuzzy subject clusters.
4.Optimally mapping the subject clusters to the subject area ontology to reveal organisation’s ‘head subjects’, ‘missing subjects’ and ‘subject gaps’.
5.Interpretation and evaluation of individual organisation profiles.
6.Combining individual organisation profiles into an aggregate profile.
7.Characterization of aggregate profiles by rule extraction.
8.Experimental verification of the method.
The proposed methodology will be applied to scientific research organisations of computer science, specifically, Computer Science (CS) departments of Universities in Portugal and UK, having as ontology of reference the ACM Classification System (http://www.acm.org/class/1998/ccs98.html).
Ongoing since January 2008, concludes in June 2011.
Participating entities: CENTRIA - UNL, Birbeck College, University of London, GECAD (ISEP).
Researchers: Boris Mirkin, Fátima Rodrigues, Fernando Jorge Duarte.
Funding entity: Fundação Ciência e Tecnologia (MCTES).
Funding: 146.837,00 €.
Principal researcher: Susana Nascimento.
Researcher: Luís Moniz Pereira.