Personalizing user-agent interaction

Autores
Schiaffino, Silvia Noemi; Amandi, Analia Adriana
Año de publicación
2006
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Interface agents are computer programs that provide personalized assistance to users with their computer-based tasks. The interface agents developed so far have focused their attention on learning a user´s preferences in a given application domain and on assisting him according to them. However, in order to personalize the interaction with users, interface agents should also learn how to best interact with each user and how to provide them assistance of the right sort at the right time. To fulfil this goal, an interface agent has to discover when the user wants a suggestion to solve a problem or deal with a given situation, when he requires only a warning about it and when he does not need any assistance at all. In this work, we propose a learning algorithm, named WoS, to tackle this problem. Our algorithm is based on the observation of a user´s actions and on a user´s reactions to the agent´s assistance actions. The WoS algorithm enables an interface agent to adapt its behavior and its interaction with a user to the user´s assistance requirements in each particular context.
Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Materia
INTERFACE AGENTS
PERSONALIZATION
USER PROFILING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/137446
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Personalizing user-agent interactionSchiaffino, Silvia NoemiAmandi, Analia AdrianaINTERFACE AGENTSPERSONALIZATIONUSER PROFILINGhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Interface agents are computer programs that provide personalized assistance to users with their computer-based tasks. The interface agents developed so far have focused their attention on learning a user´s preferences in a given application domain and on assisting him according to them. However, in order to personalize the interaction with users, interface agents should also learn how to best interact with each user and how to provide them assistance of the right sort at the right time. To fulfil this goal, an interface agent has to discover when the user wants a suggestion to solve a problem or deal with a given situation, when he requires only a warning about it and when he does not need any assistance at all. In this work, we propose a learning algorithm, named WoS, to tackle this problem. Our algorithm is based on the observation of a user´s actions and on a user´s reactions to the agent´s assistance actions. The WoS algorithm enables an interface agent to adapt its behavior and its interaction with a user to the user´s assistance requirements in each particular context.Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaElsevier Science2006-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/137446Schiaffino, Silvia Noemi; Amandi, Analia Adriana; Personalizing user-agent interaction; Elsevier Science; Knowledge-Based Systems; 19; 1; 3-2006; 43-490950-7051CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.knosys.2005.07.005info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:25:16Zoai:ri.conicet.gov.ar:11336/137446instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:25:17.036CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Personalizing user-agent interaction
title Personalizing user-agent interaction
spellingShingle Personalizing user-agent interaction
Schiaffino, Silvia Noemi
INTERFACE AGENTS
PERSONALIZATION
USER PROFILING
title_short Personalizing user-agent interaction
title_full Personalizing user-agent interaction
title_fullStr Personalizing user-agent interaction
title_full_unstemmed Personalizing user-agent interaction
title_sort Personalizing user-agent interaction
dc.creator.none.fl_str_mv Schiaffino, Silvia Noemi
Amandi, Analia Adriana
author Schiaffino, Silvia Noemi
author_facet Schiaffino, Silvia Noemi
Amandi, Analia Adriana
author_role author
author2 Amandi, Analia Adriana
author2_role author
dc.subject.none.fl_str_mv INTERFACE AGENTS
PERSONALIZATION
USER PROFILING
topic INTERFACE AGENTS
PERSONALIZATION
USER PROFILING
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Interface agents are computer programs that provide personalized assistance to users with their computer-based tasks. The interface agents developed so far have focused their attention on learning a user´s preferences in a given application domain and on assisting him according to them. However, in order to personalize the interaction with users, interface agents should also learn how to best interact with each user and how to provide them assistance of the right sort at the right time. To fulfil this goal, an interface agent has to discover when the user wants a suggestion to solve a problem or deal with a given situation, when he requires only a warning about it and when he does not need any assistance at all. In this work, we propose a learning algorithm, named WoS, to tackle this problem. Our algorithm is based on the observation of a user´s actions and on a user´s reactions to the agent´s assistance actions. The WoS algorithm enables an interface agent to adapt its behavior and its interaction with a user to the user´s assistance requirements in each particular context.
Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
description Interface agents are computer programs that provide personalized assistance to users with their computer-based tasks. The interface agents developed so far have focused their attention on learning a user´s preferences in a given application domain and on assisting him according to them. However, in order to personalize the interaction with users, interface agents should also learn how to best interact with each user and how to provide them assistance of the right sort at the right time. To fulfil this goal, an interface agent has to discover when the user wants a suggestion to solve a problem or deal with a given situation, when he requires only a warning about it and when he does not need any assistance at all. In this work, we propose a learning algorithm, named WoS, to tackle this problem. Our algorithm is based on the observation of a user´s actions and on a user´s reactions to the agent´s assistance actions. The WoS algorithm enables an interface agent to adapt its behavior and its interaction with a user to the user´s assistance requirements in each particular context.
publishDate 2006
dc.date.none.fl_str_mv 2006-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/137446
Schiaffino, Silvia Noemi; Amandi, Analia Adriana; Personalizing user-agent interaction; Elsevier Science; Knowledge-Based Systems; 19; 1; 3-2006; 43-49
0950-7051
CONICET Digital
CONICET
url http://hdl.handle.net/11336/137446
identifier_str_mv Schiaffino, Silvia Noemi; Amandi, Analia Adriana; Personalizing user-agent interaction; Elsevier Science; Knowledge-Based Systems; 19; 1; 3-2006; 43-49
0950-7051
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.knosys.2005.07.005
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844614251052793856
score 13.069144

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