Benchmarking News Recommendations: The CLEF NewsREEL Use Case

Frank Hopfgartner, Torben Brodt, Jonas Seiler, Benjamin Kille, Andreas Lommatzsch, Martha Larson, Roberto Turrin, András Serény

Research output: Contribution to journalArticleScientificpeer-review


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.
Original languageEnglish
Pages (from-to)129-136
Number of pages8
JournalACM SIGIR Forum
Issue number2
Publication statusPublished - Dec 2015


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