Sérgio R. de M. Queiroz

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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)
Resource management is challenged to apply the resources currently available and those that are to become available in the future to achieve goals efficiently. Normally, when resources are scarce, this is not an easy task, especially when the environments are real- time, partially observable, dynamic and uncertain. Despite being very common in the real(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)
We present a new algorithm capable of partitioning sets of objects by taking simultaneously into account their relational descriptions given by multiple dissimilarity matrices. The algorithm uses a nonlinear aggregation criterion, weighted Tchebycheff distances, more appropriate than linear combinations (such as weighted averages) for the construction of(More)
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