Understanding Recommendations by Reading the Clouds.

Current research has shown the important role of explanation facilities in recommender systems based on the observation that explanations can significantly influence the user-perceived quality of such a system. In this paper we present and evaluate explanation interfaces in the form of tag clouds, which are a frequently used visualization and interaction technique on the Web. We report the result of a user study in which we compare the performance of two new explanation methods based on personalized and non-personalized tag clouds with a previous explanation approach. Overall, the results show that explanations based on tag clouds are not only well-accepted by the users but can also help to improve the efficiency and effectiveness of the explanation process. Furthermore, we provide first insights on the value of personalizing explanations based on the recently-proposed concept of item-specific tag preferences.