Abstract
The multiple ways in which we rely on the information available on the web to solve increasingly more tasks encountered in everyday life has led to the question whether machines can assist us to parse the amounts of data and bring the interesting closer to us. This type of activity, most frequently, requires machines to understand human defined semantics which, fortunately, can be easily done in the present web through semantic markup. Our purpose is to develop a flexible user agent that understands the behavior of a user on the web and – on the basis of microformats – filters out the irrelevant data, presenting to the user only the information she is most interested in, while being as discreet as possible: the user is required no preference settings, no explicit feedback.
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Luca, AP., Buraga, S.C. (2009). Enhancing User Experience on the Web via Microformats-Based Recommendations. In: Filipe, J., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2008. Lecture Notes in Business Information Processing, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00670-8_24
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DOI: https://doi.org/10.1007/978-3-642-00670-8_24
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