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dc.coverage.spatialAMSTERDAM
dc.creatorROMAN-ASENJO, PABLO ENRIQUE
dc.creatorVELASQUEZ-SILVA, JUAN DOMINGO
dc.date.accessioned2017-04-27T18:49:46Z
dc.date.available2017-04-27T18:49:46Z
dc.date.issued2012
dc.identifier.issn0922-6389
dc.identifier.urihttp://hdl.handle.net/10533/196929
dc.description.abstractThe present work describes a novel approach by applying a neurophysiological theory of decision making for describing web user browsing behavior. A dynamic stochastic model of the decision making process is proposed. Such a model is based on the Leaky Competing Accumulator (LCA) model of neurophysiology. It describes the neural activity of different brain regions during the subject resolution of the decision, by means of a stochastic process that evolves until an activity reaches a given threshold that fires the decision. Such a class of stochastic processes applied to decision making has been experimentally studied for nearly forty years. In this context, a web user is confronted with deciding which link to follow according to his/her own purposes, and the process is repeated again for each visited page until leaving the web site. The parameters of the model are adjusted by means of the maximum likelihood method, using the observed sequences of pages and the time spent on each of them. It has been observed that nearly 73% of the real distribution is recovered by this method.
dc.language.isoENG
dc.publisherIOS PRESS
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.relationinstname: Conicyt
dc.relationreponame: Repositorio Digital RI2.0
dc.titleA cognitive model of the web user
dc.typeArticulo
dc.bibliographicCitation.stpage605
dc.bibliographicCitation.endpage614
dc.identifier.folioD10I1198
dc.description.citasisi1
dc.description.conicytprogramFONDEF
dc.description.emailproman@ing.uchile.cl; jvelasqu@dii.uchile.cl
dc.description.investmentarticle0
dc.identifier.isiWOS:000332936700061
dc.relation.projectidinfo:eu-repo/grantAgreement/Fondef/D10I1198
dc.relation.setinfo:eu-repo/semantics/dataset/hdl.handle.net/10533/93477
dc.rights.driverinfo:eu-repo/semantics/openAccess
dc.title.journalFRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS (PRINT)
dc.type.driverinfo:eu-repo/semantics/article
dc.description.shortconicytprogramFONDEF
dc.identifier.eissn0
dc.description.agrad0
dc.type.openaireinfo:eu-repo/semantics/publishedVersion


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