Experimental evaluation of documents classification represented using concept decomposition

The paper presents experimental evaluation of dimensionality reduction technique based on concept indexing applied on document categorization. The experiments were conducted on three collections of documents, a standard Reuters news collection in English, and two hierarchies of Web documents (Slovenian and Croatian). In the experiments on classification into the Reuters collection the method of concept indexing was more successful than latent semantic indexing for the small number of vectors on which we project the documents. We have seen that concept indexing has improved classification performance of the used Support Vector Machines classifier on some categories in all the three document collections.