| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560785 |
| ISSN: | 1405-5546 |
| Autores: | Neri Mendoza, Verónica1 Ledeneva, Yulia1 García Hernández, René Arnulfo1 Hernández Castañeda, Ángel1 |
| Instituciones: | 1Universidad Autónoma del Estado de México, Toluca de Lerdo. México |
| Año: | 2023 |
| Periodo: | Ene-Mar |
| Volumen: | 27 |
| Número: | 1 |
| Paginación: | 269-279 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | 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. |
| Keyword: | Generic, Update, Multi-document, Text summarization, Genetic algorithm |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
