Benchmarking News Recommendations

The CLEF NewsREEL Use Case

Journal article (2015)

Authors

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

M.A. Larson

Roberto Turrin ContentWise R&D

András Serény Gravity Research

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Published Date

2015-12

Language

English

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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.