Abstract
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.
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Fonseca, N.G., Rente, L., Bento, C. (2010). Selective Delivery of Points of Interest. In: de Ruyter, B., et al. Ambient Intelligence. AmI 2010. Lecture Notes in Computer Science, vol 6439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16917-5_34
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DOI: https://doi.org/10.1007/978-3-642-16917-5_34
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