The learning vector quantization algorithm applied to automatic text classification tasks

Automatic text classification is an important task for many natural language processing applications. This paper presents a neural approach to develop a text classifier based on the Learning Vector Quantization (LVQ) algorithm. The LVQ model is a classification method that uses a competitive supervi...

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Veröffentlicht in:	Neural networks 2007-08, Vol.20 (6), p.748-756
Hauptverfasser:	Martín-Valdivia, M.T., Ureña-López, L.A., García-Vega, M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Artificial intelligence Coding, codes Computer science control theory systems Exact sciences and technology Humans Information theory Information, signal and communications theory Learning Learning and adaptive systems Learning vector quantization (LVQ) Natural Language Processing Natural language processing (NLP) Neural Networks (Computer) Pattern Recognition, Automated - methods Reuters-21578 text collection Sampling, quantization SENSEVAL Signal and communications theory Telecommunications and information theory Text categorization (TC) Word sense disambiguation (WSD)
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