As we expected, with both bag-ofwords and keyword features used together, although the precision of classification using DT or NB only increases slightly, it increases significantly if we use SVM.
with 6 coarse-grained classes, the precision increases from 91.2% (table 2) to 94.1% (table 3), and with 50 fine-grained classes, it increases from 83.1% (table 2) to 85.4% using SVM (table 3).