Exploiting user context and preferences for intelligent web search

Autores
Chesñevar, Carlos Iván; Lorenzetti, Carlos M.; Maguitman, Ana Gabriela; Sagui, Fernando; Simari, Guillermo Ricardo
Año de publicación
2006
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Seeking information relevant to a topic of interest has become a common task in our daily activities. However, searching the Web using current technologies still presents many limitations. One of the main limitations is that existing tools for searching the Web restrict user queries to a small number of terms. As a result, a single query may not reflect the user information needs at a sufficient level of detail. In addition, even if longer queries were allowed, the user may not find the right terms to supply appropriate queries, or may not be willing to put the effort required to explicitly describe his or her information needs. Another limitation of today’s search tools is that they are not capable of performing qualitative inference on the suggestions they offer. For certain domains, such as news or scientific articles, a good amount of structural information can be usefully exploited to extract meaningful content. This can help sort out the material returned by a search engine and to perform a qualitative analysis to warrant some of the search results. This paper shows how to enhance current search engines capabilities by (1) taking advantage of the user context, and (2) ranking search results based on preferential criteria provided by the user. We describe ongoing research on the use of context-specific terms to refine Web search and on the use of a defeasible argumentation framework to prioritize search results.
Eje: Agentes y Sistemas Inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Intelligent agents
Search process
web search
context
argumentation
user preferences
intelligent aides
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/20749

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spelling Exploiting user context and preferences for intelligent web searchChesñevar, Carlos IvánLorenzetti, Carlos M.Maguitman, Ana GabrielaSagui, FernandoSimari, Guillermo RicardoCiencias InformáticasIntelligent agentsSearch processweb searchcontextargumentationuser preferencesintelligent aidesSeeking information relevant to a topic of interest has become a common task in our daily activities. However, searching the Web using current technologies still presents many limitations. One of the main limitations is that existing tools for searching the Web restrict user queries to a small number of terms. As a result, a single query may not reflect the user information needs at a sufficient level of detail. In addition, even if longer queries were allowed, the user may not find the right terms to supply appropriate queries, or may not be willing to put the effort required to explicitly describe his or her information needs. Another limitation of today’s search tools is that they are not capable of performing qualitative inference on the suggestions they offer. For certain domains, such as news or scientific articles, a good amount of structural information can be usefully exploited to extract meaningful content. This can help sort out the material returned by a search engine and to perform a qualitative analysis to warrant some of the search results. This paper shows how to enhance current search engines capabilities by (1) taking advantage of the user context, and (2) ranking search results based on preferential criteria provided by the user. We describe ongoing research on the use of context-specific terms to refine Web search and on the use of a defeasible argumentation framework to prioritize search results.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI)2006-06info: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/10915/20749enginfo:eu-repo/semantics/altIdentifier/isbn/950-9474-35-5info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T10:47:00Zoai:sedici.unlp.edu.ar:10915/20749Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 10:47:00.515SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Exploiting user context and preferences for intelligent web search
title Exploiting user context and preferences for intelligent web search
spellingShingle Exploiting user context and preferences for intelligent web search
Chesñevar, Carlos Iván
Ciencias Informáticas
Intelligent agents
Search process
web search
context
argumentation
user preferences
intelligent aides
title_short Exploiting user context and preferences for intelligent web search
title_full Exploiting user context and preferences for intelligent web search
title_fullStr Exploiting user context and preferences for intelligent web search
title_full_unstemmed Exploiting user context and preferences for intelligent web search
title_sort Exploiting user context and preferences for intelligent web search
dc.creator.none.fl_str_mv Chesñevar, Carlos Iván
Lorenzetti, Carlos M.
Maguitman, Ana Gabriela
Sagui, Fernando
Simari, Guillermo Ricardo
author Chesñevar, Carlos Iván
author_facet Chesñevar, Carlos Iván
Lorenzetti, Carlos M.
Maguitman, Ana Gabriela
Sagui, Fernando
Simari, Guillermo Ricardo
author_role author
author2 Lorenzetti, Carlos M.
Maguitman, Ana Gabriela
Sagui, Fernando
Simari, Guillermo Ricardo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Intelligent agents
Search process
web search
context
argumentation
user preferences
intelligent aides
topic Ciencias Informáticas
Intelligent agents
Search process
web search
context
argumentation
user preferences
intelligent aides
dc.description.none.fl_txt_mv Seeking information relevant to a topic of interest has become a common task in our daily activities. However, searching the Web using current technologies still presents many limitations. One of the main limitations is that existing tools for searching the Web restrict user queries to a small number of terms. As a result, a single query may not reflect the user information needs at a sufficient level of detail. In addition, even if longer queries were allowed, the user may not find the right terms to supply appropriate queries, or may not be willing to put the effort required to explicitly describe his or her information needs. Another limitation of today’s search tools is that they are not capable of performing qualitative inference on the suggestions they offer. For certain domains, such as news or scientific articles, a good amount of structural information can be usefully exploited to extract meaningful content. This can help sort out the material returned by a search engine and to perform a qualitative analysis to warrant some of the search results. This paper shows how to enhance current search engines capabilities by (1) taking advantage of the user context, and (2) ranking search results based on preferential criteria provided by the user. We describe ongoing research on the use of context-specific terms to refine Web search and on the use of a defeasible argumentation framework to prioritize search results.
Eje: Agentes y Sistemas Inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
description Seeking information relevant to a topic of interest has become a common task in our daily activities. However, searching the Web using current technologies still presents many limitations. One of the main limitations is that existing tools for searching the Web restrict user queries to a small number of terms. As a result, a single query may not reflect the user information needs at a sufficient level of detail. In addition, even if longer queries were allowed, the user may not find the right terms to supply appropriate queries, or may not be willing to put the effort required to explicitly describe his or her information needs. Another limitation of today’s search tools is that they are not capable of performing qualitative inference on the suggestions they offer. For certain domains, such as news or scientific articles, a good amount of structural information can be usefully exploited to extract meaningful content. This can help sort out the material returned by a search engine and to perform a qualitative analysis to warrant some of the search results. This paper shows how to enhance current search engines capabilities by (1) taking advantage of the user context, and (2) ranking search results based on preferential criteria provided by the user. We describe ongoing research on the use of context-specific terms to refine Web search and on the use of a defeasible argumentation framework to prioritize search results.
publishDate 2006
dc.date.none.fl_str_mv 2006-06
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info:eu-repo/semantics/publishedVersion
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dc.language.none.fl_str_mv eng
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dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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