If I were to build this, I would try deep belief networks. Deep learning can learn the features from a lot of text in an unsupervised manner and then correlate those features to a category with a relatively small training set, which allows it to generalize much better than traditional ANN techniques.
Geoff Hinton's claims that DBN's outperform traditional (shallow) ANN's, random forests and SVM's for any of the tasks he has tried them for (including classifying textual documents), though I have not benchmarked how well they work myself (not yet anyway!).
Geoff Hinton's claims that DBN's outperform traditional (shallow) ANN's, random forests and SVM's for any of the tasks he has tried them for (including classifying textual documents), though I have not benchmarked how well they work myself (not yet anyway!).