We propose a novel approach that combines data mining and linear programming techniques for classifying organizational units, such as research centers. We show how our proposal of clustering organizational units based on both efficiency and input/output parameters turns out to be effective in identifying groups of similar organizational units. We also propose the replacement of an expensive efficiency measurement, based on the solution of linear programs, with a simple but more efficient formula to be exploited in the clustering process. Preliminary experimental results, obtained from an analysis of research centers in the agro-food sector, show the effectiveness of our approach.
Combining linear programming techniques and clustering algorithms for the classification of Research Centers / Tagarelli, A; Trubitsyna, Irina; Greco, Sergio. - In: AI COMMUNICATIONS. - ISSN 0921-7126. - 17(3)(2004), pp. 111-122.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
Titolo: | Combining linear programming techniques and clustering algorithms for the classification of Research Centers |
Autori: | |
Data di pubblicazione: | 2004 |
Rivista: | |
Citazione: | Combining linear programming techniques and clustering algorithms for the classification of Research Centers / Tagarelli, A; Trubitsyna, Irina; Greco, Sergio. - In: AI COMMUNICATIONS. - ISSN 0921-7126. - 17(3)(2004), pp. 111-122. |
Handle: | http://hdl.handle.net/20.500.11770/141225 |
Appare nelle tipologie: | 1.1 Articolo in rivista |