If we compare the best BoW run (using the linear kernel and tf × idf -weighting) and the best BoC run (using 5,000-dimensional vectors with the polynomial kernel and tf × idf -weighting), we can see that the BoW representations barely outperform BoC: 82.77% versus 82.29%.
if we only look at the results for the ten largest categories in the Reuters-21578 collection, the situation is reversed and the BoC representations outperform BoW.