Un estudio de los métodos de reducción del frente de Pareto a una única solución aplicado al problema de resumen extractivo multi-documento

  1. Jesús M. Sánchez-Gómez
  2. Miguel Ángel Vega Rodríguez
  3. Carlos J. Pérez González
Procesamiento del lenguaje natural

ISSN: 1135-5948

Any de publicació: 2020

Número: 65

Pàgines: 21-28

Tipus: Article

Altres publicacions en: Procesamiento del lenguaje natural


SCImago Journal Rank

  • Any 2020
  • Impacte SJR de la revista: 0.149
  • Quartil major: Q3
  • Àrea: Linguistics and Language Quartil: Q3 Posició en l'àrea: 540/1150
  • Àrea: Computer Science Applications Quartil: Q4 Posició en l'àrea: 1336/2240

Índice Dialnet de Revistas

  • Any 2020
  • Impacte de la revista: 0,370
  • Àmbit: LINGÜÍSTICA Quartil: C1 Posició en l'àmbit: 8/72
  • Àmbit: FILOLOGÍAS Quartil: C1 Posició en l'àmbit: 11/327


  • Ciències Socials: B
  • Ciències Humanes: A

Scopus CiteScore

  • Any 2020
  • CiteScore de la revista: 1.0
  • Àrea: Language and Linguistics Percentil: 72
  • Àrea: Linguistics and Language Percentil: 71
  • Àrea: Computer Science Applications Percentil: 20

Journal Citation Indicator (JCI)

  • Any 2020
  • JCI de la revista: 0.18
  • Quartil major: Q4
  • Àrea: LINGUISTICS Quartil: Q4 Posició en l'àrea: 236/262


Automatic summarization methods are currently needed in many different contexts. The extractive multi-document summarization problem tries to cover the main content of a document collection and to reduce the redundant information. The best way to address this task is through a multi-objective optimization approach. The result of this approach is a set of non-dominated solutions or Pareto set. However, since only one summary is needed, the Pareto front must be reduced to a single solution. For this, several methods have been considered, such as the largest hypervolume, the consensus solution, the shortest distance to the ideal point, and the shortest distance to all points. The methods have been tested using datasets from DUC, and they have been evaluated with ROUGE metrics. The results show that consensus solution achieves the best average values.

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