S
Salvatore Corrente
Researcher at University of Catania
Publications - 74
Citations - 2078
Salvatore Corrente is an academic researcher from University of Catania. The author has contributed to research in topics: Ordinal regression & Multiple-criteria decision analysis. The author has an hindex of 21, co-authored 68 publications receiving 1555 citations. Previous affiliations of Salvatore Corrente include Polytechnic University of Turin.
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Journal ArticleDOI
Robust ordinal regression in preference learning and ranking
TL;DR: The paper clarifies the specific interpretation of the concept of preference learning adopted in ROR and MCDA, comparing it to the usual concept of preferences considered within ML.
Journal ArticleDOI
Multiple Criteria Hierarchy Process with ELECTRE and PROMETHEE
TL;DR: This paper proposes an extension of ELECTre and PROMETHEE methods to the case of the hierarchy of criteria, which was never considered before, and adapts ROR to the hierarchical versions of ELECTRE and PRomethEE methods.
Journal ArticleDOI
The SMAA-PROMETHEE method
TL;DR: The Stochastic Multicriteria Acceptability Analysis (SMAA) is proposed to apply to the family of PROMETHEE methods in order to explore the whole set of parameters compatible with some preference information provided by the Decision Maker (DM).
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A robust ranking method extending ELECTRE III to hierarchy of interacting criteria, imprecise weights and stochastic analysis
Salvatore Corrente,José Rui Figueira,Salvatore Greco,Salvatore Greco,Roman Słowiński,Roman Słowiński +5 more
TL;DR: In this paper, a methodology called Multiple Criteria Hierarchy Process (MCHP) has been proposed to handle the hierarchy of criteria in MCDA, which allows to consider preference relations with respect to a subset of criteria at any level of the hierarchy.
Reference EntryDOI
Robust Ordinal Regression
TL;DR: In this article, the basic principle of robust ordinal regression and the main multiple criteria decision methods to which it has been applied are described, in particular, UTA GMS and GRIPmethods, dealing with choice and ranking problems, then UTADIS GMS, dealing with sorting (ordinal classification) problems.