We investigate the problem of eliciting CP-nets in the well-known model of exact learning with equivalence and membership queries. The goal is to identify a preference ordering wi...
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
Abstract. We consider the problem of learning a user's ordinal preferences on a multiattribute domain, assuming that her preferences are lexicographic. We introduce a general ...
We present PLIANT, a learning system that supports adaptive assistance in an open calendaring system. PLIANT learns user preferences from the feedback that naturally occurs during...
Melinda T. Gervasio, Michael D. Moffitt, Martha E....
A neglected challenge in existing e-Learning (eL) systems is providing access to multimedia to all users regardless of environmental conditions such as diverse device capabilities,...