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Supervised Learning for Automatic Classification of Documents using Self-Organizing Maps
2000
DELOS Workshops / Conferences
Automatic Document Classification that corresponds with user-predefined classes is a challenging and widely researched area. Self-Organizing Maps (SOM) are unsupervised Artificial Neural Networks (ANN) which are mathematically characterized by transforming high-dimensional data into two-dimension representation, enabling automatic clustering of the input, while preserving higher order topology. A closely related algorithm is the Learning Vector Quantization (LVQ), which uses supervised learning
dblp:conf/delos/Goren-BarKL00
fatcat:65g6nhxjsrbczlom6wscv2z6ni