Autor según el artículo: Villa-Monte A, Lanzarini L, Bariviera A, Olivas J

Departamento: Gestió d'Empreses

Autor/es de la URV: Fernández Bariviera, Aurelio

Palabras clave: Text mining Sentence feature weighting Scoring-based representation Particle swarm optimization Extractive approach Document summarization Automatic summarization

Resumen: 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.

Áreas temáticas: Saúde coletiva Physics, multidisciplinary Physics and astronomy (miscellaneous) Physics and astronomy (all) Medicina ii Medicina i Mathematical physics Matemática / probabilidade e estatística Interdisciplinar Information systems Geociências General physics and astronomy Filosofía Engenharias iv Engenharias iii Electrical and electronic engineering Educação física Ciências biológicas i Ciência da computação Astronomia / física

Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 10994300

Direcció de correo del autor: aurelio.fernandez@urv.cat

Identificador del autor: 0000-0003-1014-1010

Fecha de alta del registro: 2023-07-31

Versión del articulo depositado: info:eu-repo/semantics/publishedVersion

Enlace a la fuente original: https://www.mdpi.com/1099-4300/21/6/617

URL Documento de licencia: http://repositori.urv.cat/ca/proteccio-de-dades/

Referencia al articulo segun fuente origial: Entropy. 21 (6):

Referencia de l'ítem segons les normes APA: Villa-Monte A, Lanzarini L, Bariviera A, Olivas J (2019). User-Oriented Summaries Using a PSO Based Scoring Optimization Method . Entropy, 21(6), -. DOI: 10.3390/e21060617

DOI del artículo: 10.3390/e21060617

Entidad: Universitat Rovira i Virgili

Año de publicación de la revista: 2019

Tipo de publicación: Journal Publications