In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
We propose a novel Co-Training method for statistical parsing. The algorithm takes as input a small corpus (9695 sentences) annotated with parse trees, a dictionary of possible le...
Namedentityrecognition isimportantinsophisticatedinformation service system such as Question Answering and Text Mining since most of the answer type and text mining unit depend on...
Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...
Abstract--In this paper we propose a new multi-view semisupervised learning algorithm called Local Co-Training (LCT). The proposed algorithm employs a set of local models with vect...