Abstract
In this paper we evaluate various approaches to a user profile modelling for news recommendation. We represent a user profile as a bag of real world entities, the user is interested in. News articles are thus recommended based on its contained concepts and not based on a text similarity. We propose several ways of such a user profile construction based on a user feedback. Different ways of a user feedback collection are compared. This paper addresses the problem of precise user modelling for information filtering.
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Acknowledgments
This work has been partially supported by the grant of The Czech Science Foundation (GAČR) P202/10/0761 and by the grant of Czech Technical University in Prague registration number SGS11/085/OHK3/1T/18.
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Lašek, I., Vojtáš, P. (2013). Evaluation of Models for Semantic Information Filtering. In: Kudělka, M., Pokorný, J., Snášel, V., Abraham, A. (eds) Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011. Advances in Intelligent Systems and Computing, vol 179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31603-6_19
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DOI: https://doi.org/10.1007/978-3-642-31603-6_19
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