Evaluation of Cross-Domain News Article Recommendations

摘要

This thesis will investigate methods to increase the utility of news article recommendation services. Access to different news providers allows us to consider cross-domain user preferences. We deal with recommender systems with continuously changing item collections. We will be able to observe user feedback from a real-world recommendation system operating on different domains. We will evaluate how results from existing data sets correspond to actual user reactions.