Keyword extracting using auto-associative neural networks

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 a new algorithm for ke...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Aquino, Germán Osvaldo, Hasperué, Waldo, Lanzarini, Laura Cristina
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2014
Materias:
Ciencias Informáticas
keyword extraction
text mining
neural networks
autoencoders
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/42284
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-42284
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
keyword extraction
text mining
neural networks
autoencoders
spellingShingle Ciencias Informáticas
keyword extraction
text mining
neural networks
autoencoders
Aquino, Germán Osvaldo
Hasperué, Waldo
Lanzarini, Laura Cristina
Keyword extracting using auto-associative neural networks
topic_facet Ciencias Informáticas
keyword extraction
text mining
neural networks
autoencoders
description 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 a new algorithm for keyword extraction. Its main goal is to extract keywords from text documents written in Spanish quickly and without requiring a large training set. This goal was achieved using auto-associative neural networks, also known as <i>autoencoders</i>, trained using only the terms designated as keywords in the training set, so that these networks can learn the features characterizing the important terms in a document.
format Objeto de conferencia
Objeto de conferencia
author Aquino, Germán Osvaldo
Hasperué, Waldo
Lanzarini, Laura Cristina
author_facet Aquino, Germán Osvaldo
Hasperué, Waldo
Lanzarini, Laura Cristina
author_sort Aquino, Germán Osvaldo
title Keyword extracting using auto-associative neural networks
title_short Keyword extracting using auto-associative neural networks
title_full Keyword extracting using auto-associative neural networks
title_fullStr Keyword extracting using auto-associative neural networks
title_full_unstemmed Keyword extracting using auto-associative neural networks
title_sort keyword extracting using auto-associative neural networks
publishDate 2014
url http://sedici.unlp.edu.ar/handle/10915/42284
work_keys_str_mv AT aquinogermanosvaldo keywordextractingusingautoassociativeneuralnetworks
AT hasperuewaldo keywordextractingusingautoassociativeneuralnetworks
AT lanzarinilauracristina keywordextractingusingautoassociativeneuralnetworks
bdutipo_str Repositorios
_version_ 1764820473521111040

Ejemplares similares