On the dimension of fuzzy preference relations

The concept of Dimension plays a key role in the context of crisp (classical) preference modelling. Dimension analysis allows a better insight of structure of individual preferences, giving a hint about the complexity of the preference modelling problem. Several attempts can be found in the literatu...

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Detalles Bibliográficos
Autores: Montero De Juan, Francisco Javier, Yáñez Gestoso, Francisco Javier, Cutello, Vincenzo
Tipo de recurso: capítulo de libro
Fecha de publicación:1998
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/60925
Acceso en línea:https://hdl.handle.net/20.500.14352/60925
Access Level:acceso abierto
Palabra clave:004.8
Fuzzy Preference Relation
Fuzzy Binary Relation.
Inteligencia artificial (Informática)
1203.04 Inteligencia Artificial
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oai_identifier_str oai:docta.ucm.es:20.500.14352/60925
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repository_id_str
spelling On the dimension of fuzzy preference relationsMontero De Juan, Francisco JavierYáñez Gestoso, Francisco JavierCutello, Vincenzo004.8Fuzzy Preference RelationFuzzy Binary Relation.Inteligencia artificial (Informática)1203.04 Inteligencia ArtificialThe concept of Dimension plays a key role in the context of crisp (classical) preference modelling. Dimension analysis allows a better insight of structure of individual preferences, giving a hint about the complexity of the preference modelling problem. Several attempts can be found in the literature in order to translate such a concept and its associated procedures into fuzzy preference models. In this paper, we shallrst of all discuss some of these approaches, showing that no more extra knowledge about the problem is sometimes attained, mainly due to some a priori introduced restrictions. Then we shall propose an alternative approach based upon the analysis of all associated crisp ®-cuts. Some consequences in related fuzzy preference modelling problems are also discussed.International Computer Science ConventionsAlpaidin, E.Universidad Complutense de Madrid19981998-01-0119981998-01-01book parthttp://purl.org/coar/resource_type/c_3248info:eu-repo/semantics/bookPartapplication/pdfhttps://hdl.handle.net/20.500.14352/60925reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/609252026-06-02T12:44:21Z
dc.title.none.fl_str_mv On the dimension of fuzzy preference relations
title On the dimension of fuzzy preference relations
spellingShingle On the dimension of fuzzy preference relations
Montero De Juan, Francisco Javier
004.8
Fuzzy Preference Relation
Fuzzy Binary Relation.
Inteligencia artificial (Informática)
1203.04 Inteligencia Artificial
title_short On the dimension of fuzzy preference relations
title_full On the dimension of fuzzy preference relations
title_fullStr On the dimension of fuzzy preference relations
title_full_unstemmed On the dimension of fuzzy preference relations
title_sort On the dimension of fuzzy preference relations
dc.creator.none.fl_str_mv Montero De Juan, Francisco Javier
Yáñez Gestoso, Francisco Javier
Cutello, Vincenzo
author Montero De Juan, Francisco Javier
author_facet Montero De Juan, Francisco Javier
Yáñez Gestoso, Francisco Javier
Cutello, Vincenzo
author_role author
author2 Yáñez Gestoso, Francisco Javier
Cutello, Vincenzo
author2_role author
author
dc.contributor.none.fl_str_mv Alpaidin, E.
Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 004.8
Fuzzy Preference Relation
Fuzzy Binary Relation.
Inteligencia artificial (Informática)
1203.04 Inteligencia Artificial
topic 004.8
Fuzzy Preference Relation
Fuzzy Binary Relation.
Inteligencia artificial (Informática)
1203.04 Inteligencia Artificial
description The concept of Dimension plays a key role in the context of crisp (classical) preference modelling. Dimension analysis allows a better insight of structure of individual preferences, giving a hint about the complexity of the preference modelling problem. Several attempts can be found in the literature in order to translate such a concept and its associated procedures into fuzzy preference models. In this paper, we shallrst of all discuss some of these approaches, showing that no more extra knowledge about the problem is sometimes attained, mainly due to some a priori introduced restrictions. Then we shall propose an alternative approach based upon the analysis of all associated crisp ®-cuts. Some consequences in related fuzzy preference modelling problems are also discussed.
publishDate 1998
dc.date.none.fl_str_mv 1998
1998-01-01
1998
1998-01-01
dc.type.none.fl_str_mv book part
http://purl.org/coar/resource_type/c_3248
dc.type.openaire.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/60925
url https://hdl.handle.net/20.500.14352/60925
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv International Computer Science Conventions
publisher.none.fl_str_mv International Computer Science Conventions
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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