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Croatian Operational Research Review, Vol. 7 No. 1, 2016.

Original scientific paper

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 orcid id orcid.org/0000-0003-4916-1844 ; 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 id orcid.org/0000-0002-7386-5991 ; Department of Mathematics, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia

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Abstract

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.

Keywords

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

Hrčak ID:

157350

URI

https://hrcak.srce.hr/157350

Publication date:

5.4.2016.

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