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Autore principale: Carlos G. Figuerola
Natura: Artículo científico
Lingua:en
Pubblicazione: Asociación Española para la Inteligencia Artificial 2004
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Accesso online:https://www.redalyc.org/articulo.oa?id=92582210
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author Carlos G. Figuerola
author_facet Carlos G. Figuerola
contents La Recuperación de Información en español y la normalizacion de términos Carlos G. Figuerola Ángel F. Zazo Emilio Rodriguez Vazquez de Aldana José Luis Alonso Berrocal Ingeniería grams stemming Information Retrieval in ectional stemming derivational stemming Most of the Information Retrieval Systems uses counts of frequencies of the words that occur in documents.Such counts entail the need of normalizing these terms. A simple normalization of characters (upper/lowercase, accents and other diacritical ones) seems insucient, since many words, by morphologic in-ection or derivation, could be grouped under an only form, when having very near semantic mean. Severalalgorithms of normalization are analyzed and tested experimentally to evaluate their e ectiveness 2004 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92582210 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.22 Vol.8
format Artículo científico
id redalyc_92582210
language en
publishDate 2004
publisher Asociación Española para la Inteligencia Artificial
spellingShingle La Recuperación de Información en español y la normalizacion de términos
Carlos G. Figuerola
Ingeniería
grams
stemming
Information Retrieval
in ectional stemming
derivational stemming
La Recuperación de Información en español y la normalizacion de términos Carlos G. Figuerola Ángel F. Zazo Emilio Rodriguez Vazquez de Aldana José Luis Alonso Berrocal Ingeniería grams stemming Information Retrieval in ectional stemming derivational stemming Most of the Information Retrieval Systems uses counts of frequencies of the words that occur in documents.Such counts entail the need of normalizing these terms. A simple normalization of characters (upper/lowercase, accents and other diacritical ones) seems insucient, since many words, by morphologic in-ection or derivation, could be grouped under an only form, when having very near semantic mean. Severalalgorithms of normalization are analyzed and tested experimentally to evaluate their e ectiveness 2004 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92582210 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.22 Vol.8
title La Recuperación de Información en español y la normalizacion de términos
topic Ingeniería
grams
stemming
Information Retrieval
in ectional stemming
derivational stemming
url https://www.redalyc.org/articulo.oa?id=92582210