Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Similares en SciELO
Compartir
Computación y Sistemas
versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546
Resumen
NERI-MENDOZA, Verónica; LEDENEVA, Yulia; GARCIA-HERNANDEZ, René Arnulfo y HERNANDEZ-CASTANEDA, Ángel. Generic and Update Multi-Document Text Summarization based on Genetic Algorithm. Comp. y Sist. [online]. 2023, vol.27, n.1, pp.269-279. Epub 16-Jun-2023. ISSN 2007-9737. https://doi.org/10.13053/cys-27-1-4538.
In this paper, we addressed the generic and update text summarization tasks of a set of documents as a combinatorial optimization problem through a genetic algorithm and unsupervised textual features. Particularly under the news domain, input documents are a set of articles of varying sizes covering the same event. The main advantage of the proposed method is that it is language-independent. The experimental results demonstrated that the method performs well for both kinds of summarization. Moreover, we calculated the heuristics for update text summarization like a benchmark to compare state-of-the-art methods.
Palabras llave : Generic; update; multi-document; text summarization; genetic algorithm.