Research project grouping and ranking by using adaptive Mahalanobis clustering

Autor:	Zeljko Turkalj, Damir Markulak, Slavica Singer, Rudolf Scitovski
Jazyk:	angličtina
Rok vydání:	2016
Předmět:	adaptive Mahalanobis clustering multi-criteria decision making evaluation project clustering Applied mathematics. Quantitative methods T57-57.97
Zdroj:	Croatian Operational Research Review, Vol 7, Iss 1, Pp 81-96 (2016)
Druh dokumentu:	article
ISSN:	1848-0225 1848-9931
DOI:	10.17535/crorr.2016.0006
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/fdaaf43c51634ff78c675afffc9dccf1 Zobrazit plný text záznamu View record in DOAJ