Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria
- Autores
- Cecchini, Rocío Luján; Lorenzetti, Carlos Martin; Maguitman, Ana Gabriela
- Año de publicación
- 2009
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- In this work we propose techniques based on single - and multi-objective evolutionary algorithms to automatically evolve a population of topical queries. The developed techniques can be applied in the implementation of a topical search system. We report on the results of different strategies that attempt to evolve conjunctive and disjunctive queries. Our analysis reveals the limitations of the single-objective approach and highlights the advantages of applying multi-objective evolutionary algorithms for the problem at hand. In addition, we observe that disjunctive queries have the potential to achieve better retrieval performance than conjunctive queries. Finally, we show that the multi-objective evolutionary approach results in better performance than a baseline and other state-of-the-art techniques for query refinement.
Fil: Cecchini, Rocío Luján. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Computación Científica; Argentina
Fil: Lorenzetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencia e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Inteligencia Artificial; Argentina
Fil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencia e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Inteligencia Artificial; Argentina - Materia
-
CONJUNCTIVE QUERIES
DISJUNCTIVE QUERIES
MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS
TOPICAL SEARCH - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/75523
Ver los metadatos del registro completo
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Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteriaCecchini, Rocío LujánLorenzetti, Carlos MartinMaguitman, Ana GabrielaCONJUNCTIVE QUERIESDISJUNCTIVE QUERIESMULTI-OBJECTIVE EVOLUTIONARY ALGORITHMSTOPICAL SEARCHhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1In this work we propose techniques based on single - and multi-objective evolutionary algorithms to automatically evolve a population of topical queries. The developed techniques can be applied in the implementation of a topical search system. We report on the results of different strategies that attempt to evolve conjunctive and disjunctive queries. Our analysis reveals the limitations of the single-objective approach and highlights the advantages of applying multi-objective evolutionary algorithms for the problem at hand. In addition, we observe that disjunctive queries have the potential to achieve better retrieval performance than conjunctive queries. Finally, we show that the multi-objective evolutionary approach results in better performance than a baseline and other state-of-the-art techniques for query refinement.Fil: Cecchini, Rocío Luján. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Computación Científica; ArgentinaFil: Lorenzetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencia e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Inteligencia Artificial; ArgentinaFil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencia e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Inteligencia Artificial; ArgentinaSociedad Iberoamericana de Inteligencia Artificial2009-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/75523Cecchini, Rocío Luján; Lorenzetti, Carlos Martin; Maguitman, Ana Gabriela; Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 13; 44; 2-2009; 14-261137-36011988-3064CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.redalyc.org/html/925/92513154003/index.htmlinfo:eu-repo/semantics/altIdentifier/url/http://journaldocs.iberamia.org/articles/620/article%20(1).pdfinfo:eu-repo/semantics/altIdentifier/url/http://journal.iberamia.org/public/Vol.1-14.html#2009info:eu-repo/semantics/altIdentifier/doi/10.4114/ia.v13i44.1042info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:56:40Zoai:ri.conicet.gov.ar:11336/75523instacron: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:34982025-09-03 09:56:40.499CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria |
title |
Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria |
spellingShingle |
Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria Cecchini, Rocío Luján CONJUNCTIVE QUERIES DISJUNCTIVE QUERIES MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS TOPICAL SEARCH |
title_short |
Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria |
title_full |
Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria |
title_fullStr |
Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria |
title_full_unstemmed |
Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria |
title_sort |
Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria |
dc.creator.none.fl_str_mv |
Cecchini, Rocío Luján Lorenzetti, Carlos Martin Maguitman, Ana Gabriela |
author |
Cecchini, Rocío Luján |
author_facet |
Cecchini, Rocío Luján Lorenzetti, Carlos Martin Maguitman, Ana Gabriela |
author_role |
author |
author2 |
Lorenzetti, Carlos Martin Maguitman, Ana Gabriela |
author2_role |
author author |
dc.subject.none.fl_str_mv |
CONJUNCTIVE QUERIES DISJUNCTIVE QUERIES MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS TOPICAL SEARCH |
topic |
CONJUNCTIVE QUERIES DISJUNCTIVE QUERIES MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS TOPICAL SEARCH |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
In this work we propose techniques based on single - and multi-objective evolutionary algorithms to automatically evolve a population of topical queries. The developed techniques can be applied in the implementation of a topical search system. We report on the results of different strategies that attempt to evolve conjunctive and disjunctive queries. Our analysis reveals the limitations of the single-objective approach and highlights the advantages of applying multi-objective evolutionary algorithms for the problem at hand. In addition, we observe that disjunctive queries have the potential to achieve better retrieval performance than conjunctive queries. Finally, we show that the multi-objective evolutionary approach results in better performance than a baseline and other state-of-the-art techniques for query refinement. Fil: Cecchini, Rocío Luján. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Computación Científica; Argentina Fil: Lorenzetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencia e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Inteligencia Artificial; Argentina Fil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencia e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Inteligencia Artificial; Argentina |
description |
In this work we propose techniques based on single - and multi-objective evolutionary algorithms to automatically evolve a population of topical queries. The developed techniques can be applied in the implementation of a topical search system. We report on the results of different strategies that attempt to evolve conjunctive and disjunctive queries. Our analysis reveals the limitations of the single-objective approach and highlights the advantages of applying multi-objective evolutionary algorithms for the problem at hand. In addition, we observe that disjunctive queries have the potential to achieve better retrieval performance than conjunctive queries. Finally, we show that the multi-objective evolutionary approach results in better performance than a baseline and other state-of-the-art techniques for query refinement. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009-02 |
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/11336/75523 Cecchini, Rocío Luján; Lorenzetti, Carlos Martin; Maguitman, Ana Gabriela; Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 13; 44; 2-2009; 14-26 1137-3601 1988-3064 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/75523 |
identifier_str_mv |
Cecchini, Rocío Luján; Lorenzetti, Carlos Martin; Maguitman, Ana Gabriela; Evolving disjunctive and conjunctive topical queries based on multi-objective optimization criteria; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 13; 44; 2-2009; 14-26 1137-3601 1988-3064 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://www.redalyc.org/html/925/92513154003/index.html info:eu-repo/semantics/altIdentifier/url/http://journaldocs.iberamia.org/articles/620/article%20(1).pdf info:eu-repo/semantics/altIdentifier/url/http://journal.iberamia.org/public/Vol.1-14.html#2009 info:eu-repo/semantics/altIdentifier/doi/10.4114/ia.v13i44.1042 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Sociedad Iberoamericana de Inteligencia Artificial |
publisher.none.fl_str_mv |
Sociedad Iberoamericana de Inteligencia Artificial |
dc.source.none.fl_str_mv |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
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