Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search

Autores
Nicolini, Ana Lucía; Lorenzetti, Carlos Martin; Maguitman, Ana Gabriela; Chesñevar, Carlos Iván
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The Internet is a cooperative and decentralized network built out of millions of participants that store and share large amounts of information with other users. Peer-to-peer systems go hand-in-hand with this huge decentralized network, where each individual node can serve content as well as request it. In this scenario, the analysis, development and testing of distributed search algorithms is a key research avenue. In particular, thematic search algorithms should lead to and benefit from the emergence of semantic communities that are the result of the interaction among participants. As a result, intelligent algorithms for neighbor selection should give rise to a logical network topology reflecting efficient communication patterns. This paper presents a series of algorithms which are specifically aimed at reducing the propagation of queries in the network, by applying a novel approach for learning peers´ interests. These algorithms were constructed in an incremental way, so that each new algorithm presents some improvements over the previous ones. Promising results were obtained through different simulations designed to test the reduction of query propagation as well as the maximization of the clustering coefficient of the emergent logical network.
Fil: Nicolini, Ana Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
Fil: Lorenzetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
Fil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
Fil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
Materia
P2p Systems
Thematic Search
Semantic Communities
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:11336/42738
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Intelligent Algorithms for Improving Communication Patterns in Thematic P2P SearchNicolini, Ana LucíaLorenzetti, Carlos MartinMaguitman, Ana GabrielaChesñevar, Carlos IvánP2p SystemsThematic SearchSemantic Communitieshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The Internet is a cooperative and decentralized network built out of millions of participants that store and share large amounts of information with other users. Peer-to-peer systems go hand-in-hand with this huge decentralized network, where each individual node can serve content as well as request it. In this scenario, the analysis, development and testing of distributed search algorithms is a key research avenue. In particular, thematic search algorithms should lead to and benefit from the emergence of semantic communities that are the result of the interaction among participants. As a result, intelligent algorithms for neighbor selection should give rise to a logical network topology reflecting efficient communication patterns. This paper presents a series of algorithms which are specifically aimed at reducing the propagation of queries in the network, by applying a novel approach for learning peers´ interests. These algorithms were constructed in an incremental way, so that each new algorithm presents some improvements over the previous ones. Promising results were obtained through different simulations designed to test the reduction of query propagation as well as the maximization of the clustering coefficient of the emergent logical network.Fil: Nicolini, Ana Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Lorenzetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaPergamon-Elsevier Science Ltd2017-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/42738Nicolini, Ana Lucía; Lorenzetti, Carlos Martin; Maguitman, Ana Gabriela; Chesñevar, Carlos Iván; Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search; Pergamon-Elsevier Science Ltd; Information Processing & Management; 53; 2; 3-2017; 388-4040306-4573CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ipm.2016.12.001info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0306457316306793info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:36:29Zoai:ri.conicet.gov.ar:11336/42738instacron: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:34982025-10-15 14:36:30.098CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search
title Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search
spellingShingle Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search
Nicolini, Ana Lucía
P2p Systems
Thematic Search
Semantic Communities
title_short Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search
title_full Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search
title_fullStr Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search
title_full_unstemmed Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search
title_sort Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search
dc.creator.none.fl_str_mv Nicolini, Ana Lucía
Lorenzetti, Carlos Martin
Maguitman, Ana Gabriela
Chesñevar, Carlos Iván
author Nicolini, Ana Lucía
author_facet Nicolini, Ana Lucía
Lorenzetti, Carlos Martin
Maguitman, Ana Gabriela
Chesñevar, Carlos Iván
author_role author
author2 Lorenzetti, Carlos Martin
Maguitman, Ana Gabriela
Chesñevar, Carlos Iván
author2_role author
author
author
dc.subject.none.fl_str_mv P2p Systems
Thematic Search
Semantic Communities
topic P2p Systems
Thematic Search
Semantic Communities
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The Internet is a cooperative and decentralized network built out of millions of participants that store and share large amounts of information with other users. Peer-to-peer systems go hand-in-hand with this huge decentralized network, where each individual node can serve content as well as request it. In this scenario, the analysis, development and testing of distributed search algorithms is a key research avenue. In particular, thematic search algorithms should lead to and benefit from the emergence of semantic communities that are the result of the interaction among participants. As a result, intelligent algorithms for neighbor selection should give rise to a logical network topology reflecting efficient communication patterns. This paper presents a series of algorithms which are specifically aimed at reducing the propagation of queries in the network, by applying a novel approach for learning peers´ interests. These algorithms were constructed in an incremental way, so that each new algorithm presents some improvements over the previous ones. Promising results were obtained through different simulations designed to test the reduction of query propagation as well as the maximization of the clustering coefficient of the emergent logical network.
Fil: Nicolini, Ana Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
Fil: Lorenzetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
Fil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
Fil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
description The Internet is a cooperative and decentralized network built out of millions of participants that store and share large amounts of information with other users. Peer-to-peer systems go hand-in-hand with this huge decentralized network, where each individual node can serve content as well as request it. In this scenario, the analysis, development and testing of distributed search algorithms is a key research avenue. In particular, thematic search algorithms should lead to and benefit from the emergence of semantic communities that are the result of the interaction among participants. As a result, intelligent algorithms for neighbor selection should give rise to a logical network topology reflecting efficient communication patterns. This paper presents a series of algorithms which are specifically aimed at reducing the propagation of queries in the network, by applying a novel approach for learning peers´ interests. These algorithms were constructed in an incremental way, so that each new algorithm presents some improvements over the previous ones. Promising results were obtained through different simulations designed to test the reduction of query propagation as well as the maximization of the clustering coefficient of the emergent logical network.
publishDate 2017
dc.date.none.fl_str_mv 2017-03
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/11336/42738
Nicolini, Ana Lucía; Lorenzetti, Carlos Martin; Maguitman, Ana Gabriela; Chesñevar, Carlos Iván; Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search; Pergamon-Elsevier Science Ltd; Information Processing & Management; 53; 2; 3-2017; 388-404
0306-4573
CONICET Digital
CONICET
url http://hdl.handle.net/11336/42738
identifier_str_mv Nicolini, Ana Lucía; Lorenzetti, Carlos Martin; Maguitman, Ana Gabriela; Chesñevar, Carlos Iván; Intelligent Algorithms for Improving Communication Patterns in Thematic P2P Search; Pergamon-Elsevier Science Ltd; Information Processing & Management; 53; 2; 3-2017; 388-404
0306-4573
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.ipm.2016.12.001
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0306457316306793
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
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
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_ 1846082830691467264
score 13.22299

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