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In text management tasks, the dimensionality reduction becomes necessary to computation and interpretability of the results generated by machine learning algorithms. This paper describes a feature extraction method called semantic mapping. Semantic mapping, sparse random mapping and PCA are applied to self-organization of document collections using self-organizing map (SOM). The behaviors of the methods...
The large volume of nowadays document collections has increased the need of fast trainable document organization systems. This paper presents and evaluates a hybrid system to self-organization of massive document collections based on self-organizing map (SOM). The hybrid system uses prototypes generated by a clustering algorithm to train the document maps, thus reducing the training time of large...
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