Fragments and text categorization

Abstract

We introduce two novel methods of text categorization in which documents are split into fragments. We conducted experiments on English, French and Czech. In all cases, the problems referred to a binary document classification. We find that both methods increase the accuracy of text categorization. For the Naïve Bayes classifier this increase is significant.