Publication at Faculty of Mathematics and Physics |
2011
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.