Intelligent algorithms for reducing query propagation in thematic P2P search

Autores
Lorenzetti, Carlos M.; Maguitman, Ana Gabriela; Chesñevar, Carlos Iván; Nicolini, Ana Lucía
Año de publicación
2013
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Information retrieval is a relevant topic in our days, espe-cially in distributed systems where thousands of participants store and share large amounts of information with other users. The analysis, development and testing of adaptive search algorithms is a key avenue to exploit the capacity of P2P systems to lead to the emergence of semantic communities that are the result of the interaction between participants. In particular, intelligent algorithms for neighbor selection should lead to the emergence of efficient communication patterns. This paper presents new algorithms which are specifically aimed at reducing query propagation overload through learning peers’ interests. Promising results were obtained through different experiments designed to test the reduction of query propagation when performing thematic search in a distributed environment.
XIV Workshop agentes y sistemas inteligentes.
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Informática
information retrieval
Electronic data interchange (EDI)
Information Systems
semantic communities
peer to peer (P2P)
Information Search and Retrieval
Intelligent agents
Algorithms
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:10915/31436

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network_name_str SEDICI (UNLP)
spelling Intelligent algorithms for reducing query propagation in thematic P2P searchLorenzetti, Carlos M.Maguitman, Ana GabrielaChesñevar, Carlos IvánNicolini, Ana LucíaCiencias InformáticasInformáticainformation retrievalElectronic data interchange (EDI)Information Systemssemantic communitiespeer to peer (P2P)Information Search and RetrievalIntelligent agentsAlgorithmsInformation retrieval is a relevant topic in our days, espe-cially in distributed systems where thousands of participants store and share large amounts of information with other users. The analysis, development and testing of adaptive search algorithms is a key avenue to exploit the capacity of P2P systems to lead to the emergence of semantic communities that are the result of the interaction between participants. In particular, intelligent algorithms for neighbor selection should lead to the emergence of efficient communication patterns. This paper presents new algorithms which are specifically aimed at reducing query propagation overload through learning peers’ interests. Promising results were obtained through different experiments designed to test the reduction of query propagation when performing thematic search in a distributed environment.XIV Workshop agentes y sistemas inteligentes.Red de Universidades con Carreras en Informática (RedUNCI)2013-10info: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/10915/31436enginfo: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:UNLP2025-09-29T10:57:56Zoai:sedici.unlp.edu.ar:10915/31436Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:57:57.168SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Intelligent algorithms for reducing query propagation in thematic P2P search
title Intelligent algorithms for reducing query propagation in thematic P2P search
spellingShingle Intelligent algorithms for reducing query propagation in thematic P2P search
Lorenzetti, Carlos M.
Ciencias Informáticas
Informática
information retrieval
Electronic data interchange (EDI)
Information Systems
semantic communities
peer to peer (P2P)
Information Search and Retrieval
Intelligent agents
Algorithms
title_short Intelligent algorithms for reducing query propagation in thematic P2P search
title_full Intelligent algorithms for reducing query propagation in thematic P2P search
title_fullStr Intelligent algorithms for reducing query propagation in thematic P2P search
title_full_unstemmed Intelligent algorithms for reducing query propagation in thematic P2P search
title_sort Intelligent algorithms for reducing query propagation in thematic P2P search
dc.creator.none.fl_str_mv Lorenzetti, Carlos M.
Maguitman, Ana Gabriela
Chesñevar, Carlos Iván
Nicolini, Ana Lucía
author Lorenzetti, Carlos M.
author_facet Lorenzetti, Carlos M.
Maguitman, Ana Gabriela
Chesñevar, Carlos Iván
Nicolini, Ana Lucía
author_role author
author2 Maguitman, Ana Gabriela
Chesñevar, Carlos Iván
Nicolini, Ana Lucía
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Informática
information retrieval
Electronic data interchange (EDI)
Information Systems
semantic communities
peer to peer (P2P)
Information Search and Retrieval
Intelligent agents
Algorithms
topic Ciencias Informáticas
Informática
information retrieval
Electronic data interchange (EDI)
Information Systems
semantic communities
peer to peer (P2P)
Information Search and Retrieval
Intelligent agents
Algorithms
dc.description.none.fl_txt_mv Information retrieval is a relevant topic in our days, espe-cially in distributed systems where thousands of participants store and share large amounts of information with other users. The analysis, development and testing of adaptive search algorithms is a key avenue to exploit the capacity of P2P systems to lead to the emergence of semantic communities that are the result of the interaction between participants. In particular, intelligent algorithms for neighbor selection should lead to the emergence of efficient communication patterns. This paper presents new algorithms which are specifically aimed at reducing query propagation overload through learning peers’ interests. Promising results were obtained through different experiments designed to test the reduction of query propagation when performing thematic search in a distributed environment.
XIV Workshop agentes y sistemas inteligentes.
Red de Universidades con Carreras en Informática (RedUNCI)
description Information retrieval is a relevant topic in our days, espe-cially in distributed systems where thousands of participants store and share large amounts of information with other users. The analysis, development and testing of adaptive search algorithms is a key avenue to exploit the capacity of P2P systems to lead to the emergence of semantic communities that are the result of the interaction between participants. In particular, intelligent algorithms for neighbor selection should lead to the emergence of efficient communication patterns. This paper presents new algorithms which are specifically aimed at reducing query propagation overload through learning peers’ interests. Promising results were obtained through different experiments designed to test the reduction of query propagation when performing thematic search in a distributed environment.
publishDate 2013
dc.date.none.fl_str_mv 2013-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/31436
url http://sedici.unlp.edu.ar/handle/10915/31436
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)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
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