We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
In many real-world applications, Euclidean distance in the original space is not good due to the curse of dimensionality. In this paper, we propose a new method, called Discrimina...
This paper shows how a text classifier's need for labeled training documents can be reduced by taking advantage of a large pool of unlabeled documents. We modify the Query-by...
The identification of network applications through observation of associated packet traffic flows is vital to the areas of network management and surveillance. Currently popular m...
Nigel Williams, Sebastian Zander, Grenville J. Arm...
Abstract. In this paper, we investigate the problem of video classification into predefined genre. The approach adopted is based on spatial and temporal descriptors derived from sh...
Vakkalanka Suresh, C. Krishna Mohan, R. Kumara Swa...