Our experimental results using co-training are significantly better than the original supervised results using the small amount of training data, and closer to that using supervised learning with a large amount of data.
our confidence-based approach balances the number of positive and negative samples and significantly reduces the error  rates for the negative samples as well, thus leading to performance improvement.