The problem of hypertext classification deals with objects possessing more complex information structure than the plain text has. Present hypertext classification systems show the...
Active learning has been successfully applied to many natural language processing tasks for obtaining annotated data in a cost-effective manner. We propose several extensions to an...
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
We describe a simple active learning heuristic which greatly enhances the generalization behavior of support vector machines (SVMs) on several practical document classification ta...