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. © 2013 Springer-Verlag.
Cite
CITATION STYLE
Lašek, I., & Vojtáš, P. (2012). Evaluation of models for semantic information filtering. In Advances in Intelligent Systems and Computing (Vol. 179 AISC, pp. 221–229). Springer Verlag. https://doi.org/10.1007/978-3-642-31603-6_19
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