An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search

Autores
Baggio, Cecilia; Cecchini, Rocío L.; Lorenzetti, Carlos M.; Maguitman, Ana Gabriela
Año de publicación
2016
Idioma
español castellano
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Topic-based information retrieval is the process of matching a topic of interest against the resources that are indexed. An approach for retrieving topicrelevant resources is to generate queries that are able to reflect the topic of interest. Multi-objective Evolutionary Algorithms have demonstrated great potential to deal with the problem of topical query generation. In an evolutionary approach to topic-based information retrieval the topic of interest is used to generate an initial population of queries, which is evolved towards successively better candidate queries. A common problem with such an approach is poor recall due to loss of genetic diversity. This work proposes a novel strategy inspired on the information theoretic notion of entropy to favor population diversity with the aim of attaining good global recall. Preliminary experiments conducted on a large dataset of labeled documents show the effectiveness of the proposed strategy.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
topic-based search
multi-objective evolutionary algorithms
diversity preservation
Query formulation
Information Search and Retrieval
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/56850
Acceder
id SEDICI_a426671fd4d5fb59dbb01dab23a1f18f
oai_identifier_str oai:sedici.unlp.edu.ar:10915/56850
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical SearchBaggio, CeciliaCecchini, Rocío L.Lorenzetti, Carlos M.Maguitman, Ana GabrielaCiencias Informáticastopic-based searchmulti-objective evolutionary algorithmsdiversity preservationQuery formulationInformation Search and RetrievalTopic-based information retrieval is the process of matching a topic of interest against the resources that are indexed. An approach for retrieving topicrelevant resources is to generate queries that are able to reflect the topic of interest. Multi-objective Evolutionary Algorithms have demonstrated great potential to deal with the problem of topical query generation. In an evolutionary approach to topic-based information retrieval the topic of interest is used to generate an initial population of queries, which is evolved towards successively better candidate queries. A common problem with such an approach is poor recall due to loss of genetic diversity. This work proposes a novel strategy inspired on the information theoretic notion of entropy to favor population diversity with the aim of attaining good global recall. Preliminary experiments conducted on a large dataset of labeled documents show the effectiveness of the proposed strategy.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2016-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf62-69http://sedici.unlp.edu.ar/handle/10915/56850spainfo:eu-repo/semantics/altIdentifier/url/http://45jaiio.sadio.org.ar/sites/default/files/ASAI-01_1.pdfinfo:eu-repo/semantics/altIdentifier/issn/2451-7585info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T09:49:33Zoai:sedici.unlp.edu.ar:10915/56850Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 09:49:34.241SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
spellingShingle An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
Baggio, Cecilia
Ciencias Informáticas
topic-based search
multi-objective evolutionary algorithms
diversity preservation
Query formulation
Information Search and Retrieval
title_short An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title_full An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title_fullStr An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title_full_unstemmed An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
title_sort An Entropy-Based Approach for Preserving Diversity in Evolutionary Topical Search
dc.creator.none.fl_str_mv Baggio, Cecilia
Cecchini, Rocío L.
Lorenzetti, Carlos M.
Maguitman, Ana Gabriela
author Baggio, Cecilia
author_facet Baggio, Cecilia
Cecchini, Rocío L.
Lorenzetti, Carlos M.
Maguitman, Ana Gabriela
author_role author
author2 Cecchini, Rocío L.
Lorenzetti, Carlos M.
Maguitman, Ana Gabriela
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
topic-based search
multi-objective evolutionary algorithms
diversity preservation
Query formulation
Information Search and Retrieval
topic Ciencias Informáticas
topic-based search
multi-objective evolutionary algorithms
diversity preservation
Query formulation
Information Search and Retrieval
dc.description.none.fl_txt_mv Topic-based information retrieval is the process of matching a topic of interest against the resources that are indexed. An approach for retrieving topicrelevant resources is to generate queries that are able to reflect the topic of interest. Multi-objective Evolutionary Algorithms have demonstrated great potential to deal with the problem of topical query generation. In an evolutionary approach to topic-based information retrieval the topic of interest is used to generate an initial population of queries, which is evolved towards successively better candidate queries. A common problem with such an approach is poor recall due to loss of genetic diversity. This work proposes a novel strategy inspired on the information theoretic notion of entropy to favor population diversity with the aim of attaining good global recall. Preliminary experiments conducted on a large dataset of labeled documents show the effectiveness of the proposed strategy.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description Topic-based information retrieval is the process of matching a topic of interest against the resources that are indexed. An approach for retrieving topicrelevant resources is to generate queries that are able to reflect the topic of interest. Multi-objective Evolutionary Algorithms have demonstrated great potential to deal with the problem of topical query generation. In an evolutionary approach to topic-based information retrieval the topic of interest is used to generate an initial population of queries, which is evolved towards successively better candidate queries. A common problem with such an approach is poor recall due to loss of genetic diversity. This work proposes a novel strategy inspired on the information theoretic notion of entropy to favor population diversity with the aim of attaining good global recall. Preliminary experiments conducted on a large dataset of labeled documents show the effectiveness of the proposed strategy.
publishDate 2016
dc.date.none.fl_str_mv 2016-09
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
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/56850
url http://sedici.unlp.edu.ar/handle/10915/56850
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://45jaiio.sadio.org.ar/sites/default/files/ASAI-01_1.pdf
info:eu-repo/semantics/altIdentifier/issn/2451-7585
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-sa/3.0/
Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-sa/3.0/
Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
dc.format.none.fl_str_mv application/pdf
62-69
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1843532272527998976
score 13.004268

Publicaciones similares