Benchmarking News Recommendations
The CLEF NewsREEL Use Case
Frank Hopfgartner (University of Glasgow)
Torben Brodt (Plista GmbH)
Jonas Seiler (Plista GmbH)
Benjamin Kille (Technical University of Berlin)
Andreas Lommatzsch (Technical University of Berlin)
Martha Larson (TU Delft - Multimedia Computing)
Roberto Turrin (ContentWise R&D)
András Serény (Gravity Research)
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Abstract
The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to evaluate and optimize news recommender algorithms. The goal is to create an algorithm that is able to generate news items that users would click, respecting a strict time constraint. The lab challenges participants to compete in either a “living lab” (Task 1) or perform an evaluation that replays recorded streams (Task 2). In this report, we discuss the objectives and challenges of the NewsREEL lab, summarize last year’s campaign and outline the main research challenges that can be addressed by participating in NewsREEL 2016.
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