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Preference disaggregation and statistical learning for multicriteria decision support: a review

Michael Doumpos, Zopounidis Konstantinos

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URIhttp://purl.tuc.gr/dl/dias/A96C320A-69BE-43E1-AAA7-580D6EAC61E1-
Identifierhttp://www.sciencedirect.com/science/article/pii/S0377221710003851-
Identifierhttps://doi.org/10.1016/j.ejor.2010.05.029-
Languageen-
Extent12 pagesen
TitlePreference disaggregation and statistical learning for multicriteria decision support: a reviewen
CreatorMichael Doumposen
CreatorΔουμπος Μιχαληςel
CreatorZopounidis Konstantinosen
CreatorΖοπουνιδης Κωνσταντινοςel
PublisherElsevieren
Content SummaryDisaggregation methods have become popular in multicriteria decision aiding (MCDA) for eliciting preferential information and constructing decision models from decision examples. From a statistical point of view, data mining and machine learning are also involved with similar problems, mainly with regard to identifying patterns and extracting knowledge from data. Recent research has also focused on the introduction of specific domain knowledge in machine learning algorithms. Thus, the connections between disaggregation methods in MCDA and traditional machine learning tools are becoming stronger. In this paper the relationships between the two fields are explored. The differences and similarities between the two approaches are identified, and a review is given regarding the integration of the two fields.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-09-
Date of Publication2011-
SubjectMultiple criteria analysisen
SubjectDisaggregation analysisen
SubjectPreference learningen
SubjectData miningen
Bibliographic CitationM. Doumpos and C. Zopounidis, "Preference disaggregation and statistical learning for multicriteria decision support: a review," Europ. J. Operat. Res., vol. 209, no. 3, pp. 203-214, Mar. 2011. doi:10.1016/j.ejor.2010.05.029en

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