SIMTEX: An Approach for Detecting and Measuring Textual Similarity based on Discourse and Semantics
Título del documento: SIMTEX: An Approach for Detecting and Measuring Textual Similarity based on Discourse and Semantics
Revue: Computación y sistemas
Base de datos: PERIÓDICA
Número de sistema: 000379431
ISSN: 1405-5546
Autores: 1
1
2
3
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:
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
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