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DBLP
Article . 2021
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Algoritmo LVQ aplicado a tareas de procesamiento del lenguaje natural

Authors: Martín Valdivia, María Teresa;

Algoritmo LVQ aplicado a tareas de procesamiento del lenguaje natural

Abstract

Tesis doctoral en Informática realizada por María Teresa Martín Valdivia bajo la dirección de los doctores L. Alfonso Ureña López (Univ. de Jaén) y Francisco Triguero Ruiz (Univ. de Málaga). El acto de defensa de tesis tuvo lugar el 7 de mayo de 2004 ante el tribunal formado por los doctores Manual Palomar Sanz (Univ. de Alicante), Amparo Ruiz Sepúlveda (Univ. de Málaga), Emilio Sanchís Arnal (Univ. Politécnica de Valencia), Horacio Rodríguez Hontoria (Univ. Politécnica de Barcelona), Manuel de Buenaga Rodríguez (Univ. Europea). La calificación obtenida fue Sobresaliente Cum Laude por unanimidad.

PhD Thesis in Computer Science written by María Teresa Martín Valdivia under the supervision of Dr. L. Alfonso Ureña López (Univ. of Jaén) and Dr. Francisco Triguero Ruiz (Univ. of Málaga). The author was examined in May 6th 2004 by the commitee formed by Dr. Manual Palomar Sanz (Univ. of Alicante), Dr. Amparo Ruiz Sepúlveda (Univ. of Málaga), Dr. Emilio Sanchís Arnal (Univ. Politécnica of Valencia), Dr. Horacio Rodríguez Hontoria (Univ. Politécnica de Barcelona), Dr. Manuel de Buenaga Rodríguez (Univ. Europea). The grade obtained was Sobresaliente Cum Laude.

Country
Spain
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Keywords

Algoritmo de aprendizaje por cuantificación vectorial, Word sense disambiguation, Reconocimiento de multipalabras, Redes neuronales, Learning Vector Quantization algorithm, Categorización de texto, Recuperación de información, Kohonen model, Multiword recognition, Fusion collection problem in cross-lingual information retrieval, Information retrieval, Desambiguación léxica, Text categorization, Fusión de documentos en recuperación de información multilingüe, Modelo de Kohonen, Neural networks

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green