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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.