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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/22661
Ver los metadatos del registro completo
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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 info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
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dc.language.none.fl_str_mv |
eng |
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eng |
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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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openAccess |
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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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