In this paper we propose PARTfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. In particular, it is...
Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
Combining multiple information sources, typically from several data streams is a very promising approach, both in experiments and to some extend in various real-life applications. ...
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
This paper shows that a detailed, although non-emotional, description of event or an action can be a reliable source for learning opinions. Empirical results show the practical uti...