We propose a novel unsupervised approach for distinguishing literal and non-literal use of idiomatic expressions. Our model combines an unsupervised and a supervised classifier. T...
Hidden Markov Model (HMM) based applications are common in various areas, but the incorporation of HMM's for anomaly detection is still in its infancy. This paper aims at cla...
In this paper we address the task of writer identification of on-line handwriting captured from a whiteboard. Different sets of features are extracted from the recorded data and u...
The problem of automatically classifying the gender of a blog author has important applications in many commercial domains. Existing systems mainly use features such as words, wor...
We present results of probabilistic tagging of Czech texts in order to show how these techniques work for one of the highly morphologically ambiguous inflective languages. After d...