SciELO - Scientific Electronic Library Online

 
vol.27 número1Performance of the Classification of Critical Residues at the Interface of BMPs Complexes Pondered with the Ground-State Energy Feature Using Random Forest ClassifierAutomatic Depression Detection in Social Networks Using Multiple User Characterizations índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • No hay artículos similaresSimilares 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.

        · texto en Inglés     · Inglés ( pdf )