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The learning vector quantization algorithm applied to automatic text classification tasks
M T Martín-Valdivia1, L A Ureña-López, M García-Vega
1Department of Computing, University of Jaén, Campus Las Lagunillas s/n, Edificio A3, Jaén E-23071, Spain. maite@ujaen.es
Summary
This study introduces a novel neural network approach using the Learning Vector Quantization (LVQ) algorithm for automatic text classification. The proposed method shows promising results for text categorization and word sense disambiguation tasks.
Area of Science:
- Natural Language Processing
- Machine Learning
- Artificial Intelligence
Background:
- Automatic text classification is crucial for numerous NLP applications.
- Existing classification systems have limitations.
- Supervised learning algorithms offer potential for improved classification.
Purpose of the Study:
- To present a neural approach for text classification using the Learning Vector Quantization (LVQ) algorithm.
- To evaluate the effectiveness of the LVQ-based classifier on text categorization and word sense disambiguation tasks.
Main Methods:
- Developed a neural network text classifier utilizing the Learning Vector Quantization (LVQ) algorithm.
- Applied the LVQ model to text categorization using the Reuters-21578 corpus.
- Applied the LVQ model to word sense disambiguation using the Senseval-3 corpus.
Main Results:
- The LVQ-based neural approach achieved promising results on both text categorization and word sense disambiguation.
- Experimental results indicate the effectiveness of the proposed method compared to other classification systems.
- The LVQ algorithm demonstrated its capability as a viable component in neural text classification.
Conclusions:
- The proposed neural approach based on the Learning Vector Quantization (LVQ) algorithm is a competitive alternative for text classification tasks.
- LVQ offers a robust supervised learning method for natural language processing applications.
- Further research can explore variations and optimizations of the LVQ algorithm for enhanced text classification performance.
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