User-Oriented Summaries Using a PSO Based Scoring Optimization Method

Automatic text summarization tools have a great impact on many fields, such as medicine, law, and scientific research in general. As information overload increases, automatic summaries allow handling the growing volume of documents, usually by assigning weights to the extracted phrases based on thei...

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Detalles Bibliográficos
Autores principales: Villa Monte, Augusto, Lanzarini, Laura Cristina, Fernández Bariviera, Aurelio, Olivas Varela, José Ángel
Formato: Articulo
Lenguaje:Inglés
Publicado: 2019
Materias:
Ciencias Informáticas
Document summarization
Extractive approach
Scoring-based representation
Sentence feature weighting
Particle swarm optimization
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/118986
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-118986
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Document summarization
Extractive approach
Scoring-based representation
Sentence feature weighting
Particle swarm optimization
spellingShingle Ciencias Informáticas
Document summarization
Extractive approach
Scoring-based representation
Sentence feature weighting
Particle swarm optimization
Villa Monte, Augusto
Lanzarini, Laura Cristina
Fernández Bariviera, Aurelio
Olivas Varela, José Ángel
User-Oriented Summaries Using a PSO Based Scoring Optimization Method
topic_facet Ciencias Informáticas
Document summarization
Extractive approach
Scoring-based representation
Sentence feature weighting
Particle swarm optimization
description Automatic text summarization tools have a great impact on many fields, such as medicine, law, and scientific research in general. As information overload increases, automatic summaries allow handling the growing volume of documents, usually by assigning weights to the extracted phrases based on their significance in the expected summary. Obtaining the main contents of any given document in less time than it would take to do that manually is still an issue of interest. In this article, a new method is presented that allows automatically generating extractive summaries from documents by adequately weighting sentence scoring features using Particle Swarm Optimization. The key feature of the proposed method is the identification of those features that are closest to the criterion used by the individual when summarizing. The proposed method combines a binary representation and a continuous one, using an original variation of the technique developed by the authors of this paper. Our paper shows that using user labeled information in the training set helps to find better metrics and weights. The empirical results yield an improved accuracy compared to previous methods used in this field.
format Articulo
Articulo
author Villa Monte, Augusto
Lanzarini, Laura Cristina
Fernández Bariviera, Aurelio
Olivas Varela, José Ángel
author_facet Villa Monte, Augusto
Lanzarini, Laura Cristina
Fernández Bariviera, Aurelio
Olivas Varela, José Ángel
author_sort Villa Monte, Augusto
title User-Oriented Summaries Using a PSO Based Scoring Optimization Method
title_short User-Oriented Summaries Using a PSO Based Scoring Optimization Method
title_full User-Oriented Summaries Using a PSO Based Scoring Optimization Method
title_fullStr User-Oriented Summaries Using a PSO Based Scoring Optimization Method
title_full_unstemmed User-Oriented Summaries Using a PSO Based Scoring Optimization Method
title_sort user-oriented summaries using a pso based scoring optimization method
publishDate 2019
url http://sedici.unlp.edu.ar/handle/10915/118986
work_keys_str_mv AT villamonteaugusto userorientedsummariesusingapsobasedscoringoptimizationmethod
AT lanzarinilauracristina userorientedsummariesusingapsobasedscoringoptimizationmethod
AT fernandezbarivieraaurelio userorientedsummariesusingapsobasedscoringoptimizationmethod
AT olivasvarelajoseangel userorientedsummariesusingapsobasedscoringoptimizationmethod
bdutipo_str Repositorios
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