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https://doi.org/10.17535/crorr.2016.0006

Research project grouping and ranking by using adaptive Mahalanobis clustering

Zeljko Turkalj ; Faculty of Economics, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
Damir Markulak ; Faculty of Civil Engineering, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
Slavica Singer ; Faculty of Economics, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
Rudolf Scitovski   ORCID icon orcid.org/0000-0002-7386-5991 ; Department of Mathematics, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia

Puni tekst: engleski, pdf (200 KB) str. 81-96 preuzimanja: 335* citiraj
APA 6th Edition
Turkalj, ., Markulak, D., Singer, S. i Scitovski, R. (2016). Research project grouping and ranking by using adaptive Mahalanobis clustering. Croatian Operational Research Review, 7 (1), 81-96. https://doi.org/10.17535/crorr.2016.0006
MLA 8th Edition
Turkalj, Zeljko, et al. "Research project grouping and ranking by using adaptive Mahalanobis clustering." Croatian Operational Research Review, vol. 7, br. 1, 2016, str. 81-96. https://doi.org/10.17535/crorr.2016.0006. Citirano 27.07.2021.
Chicago 17th Edition
Turkalj, Zeljko, Damir Markulak, Slavica Singer i Rudolf Scitovski. "Research project grouping and ranking by using adaptive Mahalanobis clustering." Croatian Operational Research Review 7, br. 1 (2016): 81-96. https://doi.org/10.17535/crorr.2016.0006
Harvard
Turkalj, ., et al. (2016). 'Research project grouping and ranking by using adaptive Mahalanobis clustering', Croatian Operational Research Review, 7(1), str. 81-96. https://doi.org/10.17535/crorr.2016.0006
Vancouver
Turkalj , Markulak D, Singer S, Scitovski R. Research project grouping and ranking by using adaptive Mahalanobis clustering. Croatian Operational Research Review [Internet]. 2016 [pristupljeno 27.07.2021.];7(1):81-96. https://doi.org/10.17535/crorr.2016.0006
IEEE
. Turkalj, D. Markulak, S. Singer i R. Scitovski, "Research project grouping and ranking by using adaptive Mahalanobis clustering", Croatian Operational Research Review, vol.7, br. 1, str. 81-96, 2016. [Online]. https://doi.org/10.17535/crorr.2016.0006

Sažetak
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.

Ključne riječi
adaptive Mahalanobis clustering; multi-criteria decision making; evaluation; project clustering

Hrčak ID: 157350

URI
https://hrcak.srce.hr/157350

Posjeta: 648 *