Although NBs are very fast classifiers requiring a small amount training data, there is a loss of accuracy due to the NBs' conditional independence assumption.
remaining documents, that are detected as "hard to be correctly classified" by the NB classifier in the use of rejection decision, are forwarded to process in a SVM classifier at the second stage, where the hard documents are represented by additional bag-of-words and topic-based features.