Print Email Facebook Twitter CLEF NewsREEL 2017 Overview Title CLEF NewsREEL 2017 Overview: Offline and Online Evaluation of Stream-based News Recommender Systems Author Kille, Benjamin (Technical University of Berlin) Lommatzsch, Andreas (Technical University of Berlin) Hopfgartner, Frank (University of Glasgow) Larson, M.A. (TU Delft Multimedia Computing; Radboud Universiteit Nijmegen) Brodt, Torben (Plista GmbH) Contributor Cappellato, Linda (editor) Ferro, Nicola (editor) Goeuriot, Lorraine (editor) Mandl, Thomas (editor) Date 2017 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 anoverview over the implemented approaches and discusses the evaluation results. In addition, the main results of Living Lab and the Replay task are explaine Subject recommender systemsnewsmulti-dimensional evaluationliving labstream-based recommender To reference this document use: http://resolver.tudelft.nl/uuid:6e51fc27-1e25-4bf7-88d6-62eed9ebced5 Publisher CEUR-WS Source CLEF 2017 Working Notes: Conference and Labs of the Evaluation Forum Event CLEF 2017 - Conference and Labs of the Evaluation Forum, 2017-09-11 → 2017-09-14, Dublin, Ireland Series CEUR Workshop Proceedings, 1613-0073, 1866 Part of collection Institutional Repository Document type conference paper Rights © 2017 Benjamin Kille, Andreas Lommatzsch, Frank Hopfgartner, M.A. Larson, Torben Brodt Files PDF 35743256.pdf 863.75 KB Close viewer /islandora/object/uuid:6e51fc27-1e25-4bf7-88d6-62eed9ebced5/datastream/OBJ/view