Because annotation is time-consuming, we design a semi-supervised learning algorithm to make use of unlabeled data under small training datasets in citation classification.
we adopt the idea of selftraining (Zhu and Goldberg, 2009) to employ unlabeled data, but select new labeled data in the process of self-training in a more reliable way by taking advantage of the ensemble learning (Opitz and Maclin, 1999) algorithm.