Most attempts to train part-of-speech taggers on a mixture of labeled and unlabeled data have failed. In this work stacked learning is used to reduce tagging to a classification t...
Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome t...
The recent years have witnessed a surge of interests in semi-supervised learning methods. A common strategy for these algorithms is to require that the predicted data labels shoul...
Blog classification (e.g., identifying bloggers' gender or age) is one of the most interesting current problems in blog analysis. Although this problem is usually solved by a...
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...