Ordering principles of digital libraries expressed in ontologies may be highly heterogeneous even within a domain and especially over different cultures. Automatic methods for mapp...
We present a simple method for language independent and task independent text categorization learning, based on character-level n-gram language models. Our approach uses simple in...
The cluster assumption is exploited by most semi-supervised learning (SSL) methods. However, if the unlabeled data is merely weakly related to the target classes, it becomes quest...
On a multi-dimensional text categorization task, we compare the effectiveness of a feature based approach with the use of a stateof-the-art sequential learning technique that has ...
Abstract. Automated Text Categorization has reached the levels of accuracy of human experts. Provided that enough training data is available, it is possible to learn accurate autom...