Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizaje

Autores
Anacleto, Valerio Adrián
Año de publicación
2003
Idioma
español castellano
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Agents that help users when they buy products on the Web promise to be a suitable way for transforming the overloaded world of web offers into a nice shop with personalized assistance. This promise depends closely on the efficiency of these agents to determine the preferences and habits of their customers. In this context, we have built an agent named Vendor that interacts with web customers. Through this agent we analyze three of the machine learning techniques that present advantageous characteristics for building user profiles. Thus, Bayesian networks, genetic algorithms, and neural networks have been compared for customer profiling.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
perfil de usuario
agentes de interfaz
Comercio electrónico
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/184496
Acceder
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizajeAnacleto, Valerio AdriánCiencias Informáticasperfil de usuarioagentes de interfazComercio electrónicoAgents that help users when they buy products on the Web promise to be a suitable way for transforming the overloaded world of web offers into a nice shop with personalized assistance. This promise depends closely on the efficiency of these agents to determine the preferences and habits of their customers. In this context, we have built an agent named Vendor that interacts with web customers. Through this agent we analyze three of the machine learning techniques that present advantageous characteristics for building user profiles. Thus, Bayesian networks, genetic algorithms, and neural networks have been compared for customer profiling.Sociedad Argentina de Informática e Investigación Operativa2003-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/184496spainfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:50:08Zoai:sedici.unlp.edu.ar:10915/184496Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:50:08.912SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizaje
title Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizaje
spellingShingle Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizaje
Anacleto, Valerio Adrián
Ciencias Informáticas
perfil de usuario
agentes de interfaz
Comercio electrónico
title_short Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizaje
title_full Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizaje
title_fullStr Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizaje
title_full_unstemmed Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizaje
title_sort Perfiles de usuario para agentes de interfaz: un análisis de técnicas de aprendizaje
dc.creator.none.fl_str_mv Anacleto, Valerio Adrián
author Anacleto, Valerio Adrián
author_facet Anacleto, Valerio Adrián
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
perfil de usuario
agentes de interfaz
Comercio electrónico
topic Ciencias Informáticas
perfil de usuario
agentes de interfaz
Comercio electrónico
dc.description.none.fl_txt_mv Agents that help users when they buy products on the Web promise to be a suitable way for transforming the overloaded world of web offers into a nice shop with personalized assistance. This promise depends closely on the efficiency of these agents to determine the preferences and habits of their customers. In this context, we have built an agent named Vendor that interacts with web customers. Through this agent we analyze three of the machine learning techniques that present advantageous characteristics for building user profiles. Thus, Bayesian networks, genetic algorithms, and neural networks have been compared for customer profiling.
Sociedad Argentina de Informática e Investigación Operativa
description Agents that help users when they buy products on the Web promise to be a suitable way for transforming the overloaded world of web offers into a nice shop with personalized assistance. This promise depends closely on the efficiency of these agents to determine the preferences and habits of their customers. In this context, we have built an agent named Vendor that interacts with web customers. Through this agent we analyze three of the machine learning techniques that present advantageous characteristics for building user profiles. Thus, Bayesian networks, genetic algorithms, and neural networks have been compared for customer profiling.
publishDate 2003
dc.date.none.fl_str_mv 2003-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/184496
url http://sedici.unlp.edu.ar/handle/10915/184496
dc.language.none.fl_str_mv spa
language spa
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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instname_str Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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