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http://hdl.handle.net/10662/13366
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Campo DC | Valor | idioma |
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dc.contributor.author | Sánchez Gómez, Jesús Manuel | - |
dc.contributor.author | Vega Rodríguez, Miguel Ángel | - |
dc.contributor.author | Pérez Sánchez, Carlos Javier | - |
dc.date.accessioned | 2022-01-14T09:22:30Z | - |
dc.date.available | 2022-01-14T09:22:30Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://hdl.handle.net/10662/13366 | - |
dc.description.abstract | Nowadays, the automatic text summarization is a highly relevant task in many contexts. In particular, query-focused summarization consists of generating a summary from one or multiple documents according to a query given by the user. Additionally, sentiment analysis and opinion mining analyze the polarity of the opinions contained in texts. These two issues are integrated in an approach to produce an opinionated summary according to the user’s query. Thereby, the query-focused sentiment-oriented extractive multi-document text summarization problem entails the optimization of different criteria, specifically, query relevance, redundancy reduction, and sentiment relevance. An adaptation of the metaheuristic population-based crow search algorithm has been designed, implemented, and tested to solve this multi-objective problem. Experiments have been carried out by using datasets from the Text Analysis Conference (TAC) datasets. Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metrics and the Pearson correlation coefficient have been used for the performance assessment. The results have reported that the proposed approach outperforms the existing methods in the scientific literature, with a percentage improvement of 75.5% for ROUGE-1 score and 441.3% for ROUGE-2 score. It also has been obtained a Pearson correlation coefficient of +0.841, reporting a strong linear positive correlation between the sentiment scores of the generated summaries and the sentiment scores of the queries of the topics. | es_ES |
dc.description.sponsorship | Work supported by Ministerio de Ciencia, Innovación y Universidades - Spain and Agencia Estatal de Investigación - Spain (Projects PID2019-107299GB-I00/AEI/10.13039/501100011033 and MTM2017-86875-C3-2-R), Junta de Extremadura - Spain (Projects GR18090 and GR18108), and European Union (European Regional Development Fund). Jesus M. Sanchez-Gomez is supported by Junta de Extremadura, Spain and European Union. (European Social Fund) under the doctoral fellowship PD18057. | es_ES |
dc.format.extent | 12 p. | es_ES |
dc.format.mimetype | application/pdf | en_US |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Multi-objective optimization | es_ES |
dc.subject | Crow search algorithm | es_ES |
dc.subject | Sentiment-oriented summarization | es_ES |
dc.subject | Query-focused summarization | es_ES |
dc.subject | Sentiment analysis | es_ES |
dc.subject | Análisis de los sentimientos | es_ES |
dc.subject | Optimización multiobjetivo | es_ES |
dc.subject | Resumen centrado en consultas | es_ES |
dc.subject | Resumen orientado al sentimiento | es_ES |
dc.title | Sentiment-oriented query-focused text summarization addressed with a multi-objective optimization approach | es_ES |
dc.type | article | es_ES |
dc.description.version | peerReviewed | es_ES |
europeana.type | TEXT | en_US |
dc.rights.accessRights | openAccess | es_ES |
dc.subject.unesco | 1209.01 Estadística Analítica | es_ES |
dc.subject.unesco | 5701.02 Documentación Automatizada | es_ES |
dc.subject.unesco | 12 Matemáticas | es_ES |
dc.subject.unesco | 3304.13 Dispositivos de Transmisión de Datos | es_ES |
europeana.dataProvider | Universidad de Extremadura. España | es_ES |
dc.identifier.bibliographicCitation | Sánchez Gómez, J.M., Vega Rodríguez, M.A., Pérez Sánchez, C.J. (2021). Sentiment-oriented query-focused text summarization addressed with a multi-objective optimization approach. Applied Soft Computing, 113(A), 107915. https://doi.org/10.1016/j.asoc.2021.107915 | es_ES |
dc.type.version | publishedVersion | es_ES |
dc.contributor.affiliation | Universidad de Extremadura. Departamento de Matemáticas | es_ES |
dc.contributor.affiliation | Universidad de Extremadura. Departamento de Tecnología de los Computadores y de las Comunicaciones | es_ES |
dc.identifier.doi | 10.1016/j.asoc.2021.107915 | - |
dc.identifier.publicationtitle | Applied Soft Computing | es_ES |
dc.identifier.publicationfirstpage | 107915-1 | es_ES |
dc.identifier.publicationlastpage | 107915-12 | es_ES |
dc.identifier.publicationvolume | 113(A) | es_ES |
dc.identifier.e-issn | 1568-4946 | - |
Colección: | DMATE - Artículos DTCYC - Artículos |
Archivos
Archivo | Descripción | Tamaño | Formato | |
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j.asoc.2021.107915.pdf | 1,51 MB | Adobe PDF | Descargar |
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