In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
The present work investigates the problem of determining a learning path inside a suitable domain ontology. The proposed approach enables the user of a web learning application to ...
Roberto Pirrone, Massimo Cossentino, Giovanni Pila...
Abstract. Kanazawa has shown that several non-trivial classes of categorial grammars are learnable in Gold’s model. We propose in this article to adapt this kind of symbolic lear...
We introduce a new bias for rule learning systems. The bias only allows a rule learner to create a rule that predicts class membership if each test of the rule in isolation is pred...
With increasingly conceiving learning as a social activity, technological support must become more aware of the social context of the individual in order to be able to provide adeq...