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Evaluation protocols for news recommender systems typically involve comparing the performance of methods to a baseline. The difference in performance ought to tell us what benefit we can expect from using a more sophisticated method. Ultimately, there is a trade-off between performance and effort in implementing and maintaining a system. This work explores what baselines have been used, what criteria baselines must fulfil, and evaluates a variety of baselines in a news recommender evaluationdblp:conf/recsys/KilleL19 fatcat:fq5sb3bm7vaglag5jr5trkcvxa