Keyword Identification in Spanish Documents using Neural Networks

Autores
Aquino, Germán Osvaldo; Lanzarini, Laura Cristina
Año de publicación
2015
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
Versión publicada
Descripción
The large amount of textual information digitally available today gives rise to the need for effective means of indexing, searching and retrieving this information. Keywords are used to describe briefly and precisely the contents of a textual document. In this paper we present an algorithm for keyword extraction from documents written in Spanish.This algorithm combines autoencoders, which are adequate for highly unbalanced classification problems, with the discriminative power of conventional binary classifiers. In order to improve its performance on larger and more diverse datasets, our algorithm trains several models of each kind through bagging.
XII Workshop Bases de Datos y Minería de Datos (WBDDM)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Neural nets
keyword extraction
autoencoders
Nivel de accesibilidad
Acceso abierto
Licencia
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/50434