Autori: Plaia, Antonella, Sciandra, Mariangela , Albano, Alessandro, Garcia Lapresta, Jose Luis
Titolo: Clustering alternatives in preference-approvals via novel pseudometrics
Periodico: Statistical methods & applications : Journal of the Italian Statistical Society
Anno: 2024 - Volume: 33 - Fascicolo: 1 - Pagina iniziale: 61 - Pagina finale: 87

Preference-approval structures combine preference rankings and approval voting for declaring opinions over a set of alternatives. In this paper, we propose a new procedure for clustering alternatives in order to reduce the complexity of the preference-approval space and provide a more accessible interpretation of data. To that end, we present a new family of pseudometrics on the set of alternatives that take into account voters’ preferences via preference-approvals. To obtain clusters, we use the Ranked k-medoids (RKM) partitioning algorithm, which takes as input the similarities between pairs of alternatives based on the proposed pseudometrics. Finally, using non-metric multidimensional scaling, clusters are represented in 2-dimensional space.




SICI: 1618-2510(2024)33:1<61:CAIPVN>2.0.ZU;2-#

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