VisDB: Database Exploration Using Multidimensional Visualization
IEEE Computer Graphics and Applications
A Metric for Selection of the Most Promising Rules
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
Evaluation of Overcluttering Prevention Techniques for Mobile Devices
IV '09 Proceedings of the 2009 13th International Conference Information Visualisation
A probabilistic model of geographic relevance
Proceedings of the 6th Workshop on Geographic Information Retrieval
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In our daily life, we are increasingly surrounded by devices that expose us to quantities of information well behind our cognitive capabilities. To overcome this problem various authors propose mechanisms capable of selecting only the most relevant pieces of information. In this paper, we propose an approach for information selection based on the concepts of relevance, selective attention and diversity. The idea is to select the most promising items in terms of surprise and usefulness and dismiss those that are less promising. We illustrate our approach with an example of an application for restaurant selection and show the first results from an initial evaluation of this system.