使用半监督学习方法中的自训练、协同训练方法，利用少量已标注样本和大量未标注样本来完成蛋白质关系抽取的任务。
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.
半监督学习：输入数据由带标记的和不带标记的组成。
Semi-Supervised Learning : Input data is a mixture of labelled and unlabelled examples.
若其最终的学习效果与全监督学习方法的效果一致或接近，则在人工成本和实现上，半监督学习方法更具有优越性。
If the ultimate effect of the semi-supervised method is the same or close to the result of supervised learning method, the semi-supervised learning is more advantages in labor costs and achievement.
如此，通过对少量已标记样本和大量未标记的样本进行学习从而建立分类器的半监督学习方法应运而生。
So, the semi-supervised learning method by learning a small number of labeling samples and a large number of samples to establish classifier came into being.
半监督学习算法同时考虑有标记和无标记数据，能显著提升学习效果。
Semi-supervised learning algorithms, which consider both labeled and unlabeled data, can improve learning effectiveness significantly.
半监督学习算法同时考虑有标记和无标记数据，能显著提升学习效果。
Semi-supervised learning algorithms, which consider both labeled and unlabeled data, can improve learning effectiveness significantly.
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