Articles producció científica> Gestió d'Empreses

User-Oriented Summaries Using a PSO Based Scoring Optimization Method

  • Identification data

    Identifier: imarina:5639536
    Authors:
    Villa-Monte A, Lanzarini L, Bariviera A, Olivas J
    Abstract:
    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.
  • Others:

    Author, as appears in the article.: Villa-Monte A, Lanzarini L, Bariviera A, Olivas J
    Department: Gestió d'Empreses
    URV's Author/s: Fernández Bariviera, Aurelio
    Keywords: Text mining Sentence feature weighting Scoring-based representation Particle swarm optimization Extractive approach Document summarization Automatic summarization
    Abstract: 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.
    Thematic Areas: 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
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 10994300
    Author's mail: aurelio.fernandez@urv.cat
    Author identifier: 0000-0003-1014-1010
    Record's date: 2023-07-31
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.mdpi.com/1099-4300/21/6/617
    Papper original source: Entropy. 21 (6):
    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
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.3390/e21060617
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2019
    Publication Type: Journal Publications
  • Keywords:

    Electrical and Electronic Engineering,Information Systems,Mathematical Physics,Physics and Astronomy (Miscellaneous),Physics, Multidisciplinary
    Text mining
    Sentence feature weighting
    Scoring-based representation
    Particle swarm optimization
    Extractive approach
    Document summarization
    Automatic summarization
    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
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