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Learning to assess from pair-wise comparisons

dc.contributor.authorDíez Peláez, Jorge 
dc.contributor.authorCoz Velasco, Juan José del 
dc.contributor.authorLuaces Rodríguez, Óscar 
dc.contributor.authorGoyache, Félix
dc.contributor.authorAlonso González, Jaime 
dc.contributor.authorPeña, A. M.
dc.contributor.authorBahamonde Rionda, Antonio 
dc.date.accessioned2015-06-16T09:58:24Z
dc.date.available2015-06-16T09:58:24Z
dc.date.issued2002
dc.identifier.urihttp://hdl.handle.net/10651/31247
dc.description.abstractIn this paper we present an algorithm for learning a function able to assess objects. We assume that our teachers can provide a collection of pairwise comparisons but encounter certain difficulties in assigning a number to the qualities of the objects considered. This is a typical situation when dealing with food products, where it is very interesting to have repeatable, reliable mechanisms that are as objective as possible to evaluate quality in order to provide markets with products of a uniform quality. The same problem arises when we are trying to learn user preferences in an information retrieval system or in configuring a complex device. The algorithm is implemented using a growing variant of Kohonen’s Self-Organizing Maps (growing neural gas), and is tested with a variety of data sets to demonstrate the capabilities of our approachspa
dc.format.extentp. 481-490spa
dc.language.isoengspa
dc.publisherSpringerspa
dc.relation.ispartofAdvances in Artificial Intelligence—IBERAMIA 2002spa
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleLearning to assess from pair-wise comparisonsspa
dc.typeconference outputspa
dc.rights.accessRightsopen accessspa


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CC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
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