Combining Content-based and Collaborative Filtering for Personalized Sports News Recommendations

Sports news are a special case in the field of news recommendations as readers often come with a strong emotional attachment to selected sports, teams or players. Furthermore, the interest in a topic can suddenly change if, for example, an important sports event is taking place. In this work, we present a hybrid sports news recommender system that combines content-based recommendations with collaborative filtering. We developed a recommender dashboard and integrated it into the Sport1.de website. In a user study, we evaluated our solution. Results show that a pure content-based approach delivers accurate news recommendations and the users confirm our recommender dashboard a high usability. Nevertheless, the collaborative filtering component of our hybrid approach is necessary to increase the diversity of the recommendations and to recommend older articles if they are of special importance to the user.