Research project grouping and ranking by using adaptive Mahalanobis clustering (CROSBI ID 227207)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Turkalj, Željko ; Markulak, Damir ; Singer, Slavica ; Scitovski, Rudolf
engleski
Research project grouping and ranking by using adaptive Mahalanobis clustering
The paper discusses the problem of grouping and ranking of research projects submitted for a call. The projects are grouped into clusters based on the assessment obtained in the review procedure and by using the adaptive Mahalanobis clustering method as a special case of the Expectation Maximization algorithm. The cluster of projects assessed as best is specially analyzed and ranked. The paper outlines several possibilities for the use of data obtained in the review procedure, and the proposed method is illustrated with the example of internal research projects at the University of Osijek.
adaptive Mahalanobis clustering ; multi-criteria decision making ; evaluation ; project clustering
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Podaci o izdanju
Povezanost rada
Matematika, Računarstvo