Incremental methods for context-basedWeb retrieval

Autores
Lorenzetti, Carlos M.; Sagui, Fernando; Maguitman, Ana Gabriela; Chesñevar, Carlos Iván; Simari, Guillermo Ricardo
Año de publicación
2006
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Intelligent search depends on effective methods for identifying the information needs of a user and making relevant information resources available when needed. Reflecting user context has long been recognized as a key aspect to realizing the potential of intelligent Web search. This paper proposes a theoretical basis for better understanding the role of context in Web retrieval. It addresses the problem of identifying context-specific terms, finding relevant information sources, and automatically formulating and refining queries. We describe ongoing research on the use of incremental methods to retrieve relevant content through two main approaches. The first, feed-based, periodically checks for new relevant items in specific websites by accessing RSS feeds. The second, query-based, incrementally formulates queries, which are submitted to search interfaces (e.g., major search engines or individual search forms). We discuss the technical challenges imposed by these approaches, outline our system architecture, and present preliminary evaluations of the proposed techniques.
VII Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
web search
context
RSS feeds
Search process
Query formulation
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:10915/22661

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network_name_str SEDICI (UNLP)
spelling Incremental methods for context-basedWeb retrievalLorenzetti, Carlos M.Sagui, FernandoMaguitman, Ana GabrielaChesñevar, Carlos IvánSimari, Guillermo RicardoCiencias Informáticasweb searchcontextRSS feedsSearch processQuery formulationIntelligent search depends on effective methods for identifying the information needs of a user and making relevant information resources available when needed. Reflecting user context has long been recognized as a key aspect to realizing the potential of intelligent Web search. This paper proposes a theoretical basis for better understanding the role of context in Web retrieval. It addresses the problem of identifying context-specific terms, finding relevant information sources, and automatically formulating and refining queries. We describe ongoing research on the use of incremental methods to retrieve relevant content through two main approaches. The first, feed-based, periodically checks for new relevant items in specific websites by accessing RSS feeds. The second, query-based, incrementally formulates queries, which are submitted to search interfaces (e.g., major search engines or individual search forms). We discuss the technical challenges imposed by these approaches, outline our system architecture, and present preliminary evaluations of the proposed techniques.VII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2006-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1243-1254http://sedici.unlp.edu.ar/handle/10915/22661enginfo: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:UNLP2025-10-15T10:47:46Zoai:sedici.unlp.edu.ar:10915/22661Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 10:47:46.967SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Incremental methods for context-basedWeb retrieval
title Incremental methods for context-basedWeb retrieval
spellingShingle Incremental methods for context-basedWeb retrieval
Lorenzetti, Carlos M.
Ciencias Informáticas
web search
context
RSS feeds
Search process
Query formulation
title_short Incremental methods for context-basedWeb retrieval
title_full Incremental methods for context-basedWeb retrieval
title_fullStr Incremental methods for context-basedWeb retrieval
title_full_unstemmed Incremental methods for context-basedWeb retrieval
title_sort Incremental methods for context-basedWeb retrieval
dc.creator.none.fl_str_mv Lorenzetti, Carlos M.
Sagui, Fernando
Maguitman, Ana Gabriela
Chesñevar, Carlos Iván
Simari, Guillermo Ricardo
author Lorenzetti, Carlos M.
author_facet Lorenzetti, Carlos M.
Sagui, Fernando
Maguitman, Ana Gabriela
Chesñevar, Carlos Iván
Simari, Guillermo Ricardo
author_role author
author2 Sagui, Fernando
Maguitman, Ana Gabriela
Chesñevar, Carlos Iván
Simari, Guillermo Ricardo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
web search
context
RSS feeds
Search process
Query formulation
topic Ciencias Informáticas
web search
context
RSS feeds
Search process
Query formulation
dc.description.none.fl_txt_mv Intelligent search depends on effective methods for identifying the information needs of a user and making relevant information resources available when needed. Reflecting user context has long been recognized as a key aspect to realizing the potential of intelligent Web search. This paper proposes a theoretical basis for better understanding the role of context in Web retrieval. It addresses the problem of identifying context-specific terms, finding relevant information sources, and automatically formulating and refining queries. We describe ongoing research on the use of incremental methods to retrieve relevant content through two main approaches. The first, feed-based, periodically checks for new relevant items in specific websites by accessing RSS feeds. The second, query-based, incrementally formulates queries, which are submitted to search interfaces (e.g., major search engines or individual search forms). We discuss the technical challenges imposed by these approaches, outline our system architecture, and present preliminary evaluations of the proposed techniques.
VII Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Intelligent search depends on effective methods for identifying the information needs of a user and making relevant information resources available when needed. Reflecting user context has long been recognized as a key aspect to realizing the potential of intelligent Web search. This paper proposes a theoretical basis for better understanding the role of context in Web retrieval. It addresses the problem of identifying context-specific terms, finding relevant information sources, and automatically formulating and refining queries. We describe ongoing research on the use of incremental methods to retrieve relevant content through two main approaches. The first, feed-based, periodically checks for new relevant items in specific websites by accessing RSS feeds. The second, query-based, incrementally formulates queries, which are submitted to search interfaces (e.g., major search engines or individual search forms). We discuss the technical challenges imposed by these approaches, outline our system architecture, and present preliminary evaluations of the proposed techniques.
publishDate 2006
dc.date.none.fl_str_mv 2006-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
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dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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