Abstract

One of the goals of recommender systems research is to provide insights and methods that can be used by practitioners to build real-world systems that deliver high-quality recommendations to actual people based on their genuine interests and needs. In this case study paper, we report on our experience trying to apply the news recommendation literature to build POPROX, a live platform for news recommendation research, and reflect on the extent to which the current state of research supports system-building efforts. Our experience highlights several unexpected challenges encountered in building personalization features that are commonly found in products from news aggregators and publishers, and shows how those difficulties are connected to surprising gaps in the literature. Finally, we offer a set of lessons for practical applications and highlight opportunities to make future news recommendation research more applicable and impactful.

Links

• POPROX