The rank aggregation problem can be summarized as the problem of aggregating individual preferences expressed by a set of judges to obtain a ranking that represents the best synthesis of their choices. Several approaches for handling this problem have been proposed and are generally linked with either axiomatic frameworks or alternative strategies. In this paper, we present a new definition of median ranking and frame it within the Kemeny’s axiomatic framework. Moreover, we show the usefulness of our approach in a practical case about triage prioritization.

Median constrained bucket order rank aggregation / D'Ambrosio, Antonio; Iorio, Carmela; Staiano, Michele; Siciliano, Roberta. - In: COMPUTATIONAL STATISTICS. - ISSN 0943-4062. - 34:2(2019), pp. 787-802. [10.1007/s00180-018-0858-z]

Median constrained bucket order rank aggregation

Antonio D’Ambrosio
;
Carmela Iorio;Michele Staiano;Roberta Siciliano
2019

Abstract

The rank aggregation problem can be summarized as the problem of aggregating individual preferences expressed by a set of judges to obtain a ranking that represents the best synthesis of their choices. Several approaches for handling this problem have been proposed and are generally linked with either axiomatic frameworks or alternative strategies. In this paper, we present a new definition of median ranking and frame it within the Kemeny’s axiomatic framework. Moreover, we show the usefulness of our approach in a practical case about triage prioritization.
2019
Median constrained bucket order rank aggregation / D'Ambrosio, Antonio; Iorio, Carmela; Staiano, Michele; Siciliano, Roberta. - In: COMPUTATIONAL STATISTICS. - ISSN 0943-4062. - 34:2(2019), pp. 787-802. [10.1007/s00180-018-0858-z]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/725148
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