Intelligent automatic generation of text summaries with Soft Computing techniques

Autores
Villa Monte, Augusto
Año de publicación
2019
Idioma
español castellano
Tipo de recurso
reseña artículo
Estado
versión publicada
Descripción
This thesis develops two different strategies to build automatic summaries of texts using Soft Computing techniques. The first uses a Particle Swarm Optimization technique that, from the vectorial representation of the texts, constructs an extractive summary combining adequately several punctuation metrics. The second strategy is related to the study of causality inspired with the management of uncertainty by the Fuzzy Logic. Here, the analysis of the texts is carried out through the construction of a graph by means of which the most important causal relationships are obtained together with the temporal restrictions that affect their interpretation. Both strategies fundamentally imply the classification of the information and reduce the volume of the text considering the recipient of the summary constructed in each case.
Es revisión de: http://sedici.unlp.edu.ar/handle/10915/74098
Tesis de Doctorado presentada por el autor el 18 de marzo de 2019 en la Universidad Nacional de La Plata para la obtención del título de Doctor en Ciencias Informáticas.
Facultad de Informática
Materia
Ciencias Informáticas
soft computing
summaries of texts
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/74468

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spelling Intelligent automatic generation of text summaries with Soft Computing techniquesVilla Monte, AugustoCiencias Informáticassoft computingsummaries of textsThis thesis develops two different strategies to build automatic summaries of texts using Soft Computing techniques. The first uses a Particle Swarm Optimization technique that, from the vectorial representation of the texts, constructs an extractive summary combining adequately several punctuation metrics. The second strategy is related to the study of causality inspired with the management of uncertainty by the Fuzzy Logic. Here, the analysis of the texts is carried out through the construction of a graph by means of which the most important causal relationships are obtained together with the temporal restrictions that affect their interpretation. Both strategies fundamentally imply the classification of the information and reduce the volume of the text considering the recipient of the summary constructed in each case.Es revisión de: http://sedici.unlp.edu.ar/handle/10915/74098Tesis de Doctorado presentada por el autor el 18 de marzo de 2019 en la Universidad Nacional de La Plata para la obtención del título de Doctor en Ciencias Informáticas.Facultad de Informática2019-04info:eu-repo/semantics/reviewinfo:eu-repo/semantics/publishedVersionRevisionhttp://purl.org/coar/resource_type/c_dcae04bcinfo:ar-repo/semantics/resenaArticuloapplication/pdf91-92http://sedici.unlp.edu.ar/handle/10915/74468spainfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/altIdentifier/doi/10.24215/16666038.19.e09info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:53:40Zoai:sedici.unlp.edu.ar:10915/74468Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:53:40.558SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Intelligent automatic generation of text summaries with Soft Computing techniques
title Intelligent automatic generation of text summaries with Soft Computing techniques
spellingShingle Intelligent automatic generation of text summaries with Soft Computing techniques
Villa Monte, Augusto
Ciencias Informáticas
soft computing
summaries of texts
title_short Intelligent automatic generation of text summaries with Soft Computing techniques
title_full Intelligent automatic generation of text summaries with Soft Computing techniques
title_fullStr Intelligent automatic generation of text summaries with Soft Computing techniques
title_full_unstemmed Intelligent automatic generation of text summaries with Soft Computing techniques
title_sort Intelligent automatic generation of text summaries with Soft Computing techniques
dc.creator.none.fl_str_mv Villa Monte, Augusto
author Villa Monte, Augusto
author_facet Villa Monte, Augusto
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
soft computing
summaries of texts
topic Ciencias Informáticas
soft computing
summaries of texts
dc.description.none.fl_txt_mv This thesis develops two different strategies to build automatic summaries of texts using Soft Computing techniques. The first uses a Particle Swarm Optimization technique that, from the vectorial representation of the texts, constructs an extractive summary combining adequately several punctuation metrics. The second strategy is related to the study of causality inspired with the management of uncertainty by the Fuzzy Logic. Here, the analysis of the texts is carried out through the construction of a graph by means of which the most important causal relationships are obtained together with the temporal restrictions that affect their interpretation. Both strategies fundamentally imply the classification of the information and reduce the volume of the text considering the recipient of the summary constructed in each case.
Es revisión de: http://sedici.unlp.edu.ar/handle/10915/74098
Tesis de Doctorado presentada por el autor el 18 de marzo de 2019 en la Universidad Nacional de La Plata para la obtención del título de Doctor en Ciencias Informáticas.
Facultad de Informática
description This thesis develops two different strategies to build automatic summaries of texts using Soft Computing techniques. The first uses a Particle Swarm Optimization technique that, from the vectorial representation of the texts, constructs an extractive summary combining adequately several punctuation metrics. The second strategy is related to the study of causality inspired with the management of uncertainty by the Fuzzy Logic. Here, the analysis of the texts is carried out through the construction of a graph by means of which the most important causal relationships are obtained together with the temporal restrictions that affect their interpretation. Both strategies fundamentally imply the classification of the information and reduce the volume of the text considering the recipient of the summary constructed in each case.
publishDate 2019
dc.date.none.fl_str_mv 2019-04
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