Document classification is a key task for many text mining applications. However, traditional text classification requires labeled data to construct reliable and accurate classifie...
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
Document classification presents difficult challenges due to the sparsity and the high dimensionality of text data, and to the complex semantics of the natural language. The tradi...
This paper presents novel methods for classifying images based on knowledge discovered from annotated images using WordNet. The novelty of this work is the automatic class discove...
This paper presents our work on automatically detecting moving rigid text in digital videos. The temporal information is obtained by dividing a video frame into sub-blocks and cal...