We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
The recognition of script in historical documents requires suitable techniques in order to identify single words. Segmentation of lines and words is a challenging task because lin...
It is shown that basic language processes such as the production of free word associations and the generation of synonyms can be simulated using statistical models that analyze th...
This paper presents Domain Relevance Estimation (DRE), a fully unsupervised text categorization technique based on the statistical estimation of the relevance of a text with respe...
We present a corpus{based approach to word{sense disambiguation that only requires information that can be automatically extracted from untagged text. We use unsupervised techniqu...