Improved Semantic Mapping and SOM Applied to Document Organization

This paper presents and evaluates a new version of the Semantic Mapping method applied to the construction of a hybrid document organization system based on Self-Organizing Maps. The hybrid system uses reduced document vectors generated by Semantic Mapping to training the SOM map, thus reducing the training time without compromising the quality of the document map. We test the hybrid system with different versions of Semantic Mapping and the correspondent SOM system in document organization of the Reuters-21758 v1.0 and 20 Newsgroup collections. The performance of the systems was measured in terms of text categorization effectiveness on test set and training time. The experimental results show that new version of Semantic Mapping is superior to previous one.