Abstract:

Semi-supervised learning methods including self-training and co-training were shown in the task of PPI on how to alleviate the tag burden as much as possible. On self training a word feature based SVM model was applied; In co-training word feature and dependency tree based SVM models were used. Experiments on four copra showed that the two methods were effective in reducing the amount of labeling PPI(protein-protein interaction). Comparing self -training to-cotraining can be more effective by using two separated views.