Description of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...

A common problem with feature selection is to establish how many features should be retained at least so that important information is not lost. We describe a method for choosing this number that makes use of Support Vector Machines. The method is based on controlling an angle by which the decision hyperplane is tilt due to feature selection. Experiments were performed on three text datasets generated from a Wikipedia dump. Amount...

We present a tool for common sense knowledge acquisition in form of a twenty questions game. The described approach uses WordNet dictionary, which rich taxonomy allows to keep cognitive economy and accelerate knowledge propagation, although sometimes inferences made on hierarchical relations result in noise. We extend the dictionary with common sense assertions acquired during the games played with humans. The facts added to the...