The paper proposes a technique based on a combined approach of data mining algorithms and linear programming methods for classifying organizational units, such as research centers. We exploit clustering algorithms for grouping information concerning the scientific activi\-ty of research centers. We also show that the replacement of an expensive efficiency measurement, based on the solution of linear programs, with a simple formula allows to efficiently compute clusters of very good quality. Some initial experimental results, obtained from the analysis of research centers in the agro-food sector, show the effectiveness of our approach, both from an efficiency and a quality-of-results viewpoint.

Mining Scientific Results to Measure the Efficiency of Research Centers

TAGARELLI, Andrea;I. Trubitsyna;
2003-01-01

Abstract

The paper proposes a technique based on a combined approach of data mining algorithms and linear programming methods for classifying organizational units, such as research centers. We exploit clustering algorithms for grouping information concerning the scientific activi\-ty of research centers. We also show that the replacement of an expensive efficiency measurement, based on the solution of linear programs, with a simple formula allows to efficiently compute clusters of very good quality. Some initial experimental results, obtained from the analysis of research centers in the agro-food sector, show the effectiveness of our approach, both from an efficiency and a quality-of-results viewpoint.
2003
88-498-0629-9
clustering; data envelopment analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/180176
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