CLEF NewsREEL 2017 Overview
Offline and Online Evaluation of Stream-based News Recommender Systems
Benjamin Kille (Technical University of Berlin)
Andreas Lommatzsch (Technical University of Berlin)
Frank Hopfgartner (University of Glasgow)
M.A. Larson (TU Delft - Multimedia Computing, Radboud Universiteit Nijmegen)
Torben Brodt (Plista GmbH)
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Abstract
The CLEF NewsREEL challenge allows researchers to evaluate news recommendation algorithms both online (NewsREEL Live) and offline (News-REEL Replay). Compared with the previous year NewsREEL challenged participants with a higher volume of messages and new news portals. In the 2017 edition of the CLEF NewsREEL challenge a wide variety of new approaches have been implemented ranging from the use of existing machine learning frameworks, to ensemble methods to the use of deep neural networks. This paper gives an
overview over the implemented approaches and discusses the evaluation results. In addition, the main results of Living Lab and the Replay task are explaine