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dc.contributor.authorLarsen, Henrik Legind
dc.contributor.authorMarín Ruíz, Nicolás
dc.contributor.authorMartín Bautista, Maria José
dc.contributor.authorVila Miranda, María Amparo
dc.date.accessioned2007-09-27T11:27:30Z
dc.date.available2007-09-27T11:27:30Z
dc.date.issued2000
dc.identifier.issn1134-5632
dc.identifier.urihttp://hdl.handle.net/2099/3583
dc.description.abstractMost of the techniques used in text classification are determined by the occurrences of the words (terms) appearing in the documents, combined with the user feedback over the documents retrieved. However, in our model, the most relevant terms will be selected from a previous fuzzy classification given by the genetic algorithm guided by the user feedback, but using techniques from Machine Learning. A feature selection process is carried out through a Genetic Algorithm in order to find the most discriminatory terms to be stored as the user profile.
dc.format.extent275-286
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
dc.relation.ispartofMathware & soft computing . 2000 Vol. 7 Núm. 2 [ -3 ]
dc.rightsReconeixement-NoComercial-CompartirIgual 3.0 Espanya
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.otherUser profiles
dc.subject.otherFuzzy classification
dc.subject.otherFeature selection
dc.subject.otherGenetic Algorithms
dc.subject.otherWorld Wide Web
dc.titleUsing genetic feature selection for optimizing user profiles
dc.typeArticle
dc.subject.lemacInformàtica aplicada
dc.subject.lemacProcessament electrònic de dades
dc.subject.lemacAprenentatge automàtic -- Algorismes
dc.subject.amsClassificació AMS::68 Computer science::68U Computing methodologies and applications
dc.rights.accessOpen Access


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