Conference Papers

Evaluation of Cross-Domain News Article Recommendations

AuthorBenjamin Kille
Source21st Conference on User Modeling, Adaptation and Personalization (UMAP'13), Rome, Italy 
LinksBibTeX 

This thesis will investigate methods to increase the utility of news article recommendation services. Access to di erent 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 di erent domains. We will evaluate how results from existing data sets correspond to actual user reactions.