SciELO - Scientific Electronic Library Online

 
vol.10 número2Módulo para la evaluación de competencias a través de un Sistema de Laboratorios a DistanciasSIGESPRO: Sistemas de Información Geográfica para controlar proyectos índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

  • No hay articulos citadosCitado por SciELO

Links relacionados

  • No hay articulos similaresSimilares en SciELO

Compartir


Revista Cubana de Ciencias Informáticas

versión On-line ISSN 2227-1899

Resumen

TORRES LOPEZ, Carmen  y  ARCO GARCIA, Leticia. Textual representation in semantic vector space. Rev cuba cienc informat [online]. 2016, vol.10, n.2, pp.148-180. ISSN 2227-1899.

The vector space model represents textual documents via vectors of terms, but it cannot represent semantic relationships between words. Semantic vector spaces are based on the idea that the meaning of a word can be learned from a linguistic environment and have two approaches, the distributional semantics and compositional semantics. The first approach analyzes the meaning of individual words and the second approach the meaning of phrases, sentences and paragraphs. This review presents the main models of these approaches and the computational tools that implement them. This study bring to a conclusion that the incorporation of semantic representations in the different tools that perform textual analysis is necessary, essentially researchers have obtained best representations that make prediction of contexts in the case of distributional models and the ones that incorporate models based on neural networks for compositional models.

Palabras clave : text mining; semantic vector space; distributional semantics; compositional semantics.

        · resumen en Español     · texto en Español     · Español ( pdf )

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons