We describe research on data-drive refinement and evaluation of a probabilistic model of student learning for an educational game on number factorization. The model is to be used b...
Most of the approaches for dealing with uncertainty in the Semantic Web rely on the principle that this uncertainty is already asserted. In this paper, we propose a new approach t...
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Recent advances in e-learning techonologies and web services make realistic the idea that courseware for personalized e-learning can be built by dynamic composition of distributed ...
Simona Colucci, Tommaso Di Noia, Eugenio Di Sciasc...
In this paper we extend the PAC learning algorithm due to Clark and Thollard for learning distributions generated by PDFA to automata whose transitions may take varying time length...