Revista: | Computación y sistemas |
Base de datos: | PERIÓDICA |
Número de sistema: | 000379431 |
ISSN: | 1405-5546 |
Autores: | Cunha, Iria da1 Vivaldi, Jorge1 Torres Moreno, Juan Manuel2 Sierra, Gerardo3 |
Instituciones: | 1Universidad Pompeu Fabra, Barcelona. España 2Universite d'Avignon et des Pays de Vaucluse, Avignon, Vaucluse. Francia 3Universidad Nacional Autónoma de México, Instituto de Ingeniería, México, Distrito Federal. México |
Año: | 2014 |
Periodo: | Jul-Sep |
Volumen: | 18 |
Número: | 3 |
Paginación: | 505-516 |
País: | México |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Enfoque: | Analítico, descriptivo |
Resumen en inglés | Nowadays automatic systems for detecting and measuring textual similarity are being developed, in order to apply them to different tasks in the field of Natural Language Processing (NLP). Currently, these systems use surface linguistic features or statistical information. Nowadays, few researchers use deep linguistic information. In this work, we present an algorithm for detecting and measuring textual similarity that takes into account information offered by discourse relations of Rhetorical Structure Theory (RST), and lexical-semantic relations included in EuroWordNet. We apply the algorithm, called SIMTEX, to texts written in Spanish, but the methodology is potentially language-independent |
Disciplinas: | Ciencias de la computación, Literatura y lingüística |
Palabras clave: | Inteligencia artificial, Análisis del discurso, Lingüística aplicada, Similitud textual, Paráfrasis, Semántica |
Keyword: | Computer science, Literature and linguistics, Artificial intelligence, Applied linguistics, Discourse analysis, Textual similarity, Paraphrase, Semantics |
Texto completo: | Texto completo (Ver HTML) |