Sérgio R. de M. Queiroz

Learn More
The enormous number of questions needed to acquire a full preference model when the size of the outcome space is large forces us to work with partial models that approximate the user's preferences. In this way we must devise elicitation strategies that focus on the most important questions and at the same time do not need to enumerate the outcome space. In(More)
In recent years, recommender systems have achieved great success. Popular sites give thousands of recommendations every day. However, despite the fact that many activities are carried out in groups, like going to the theater with friends, these systems are focused on recommending items for sole users. This brings out the need of systems capable of(More)
  • 1