Evaluation of Models for Semantic Information Filtering.

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.