CLEF 2017 NewsREEL Overview: Offline and Online Evaluation of Stream-based News Recommender Systems

Kille, B., Lommatzsch, A., Hopfgartner, F. , Larson, M. and Brodt, T. (2017) CLEF 2017 NewsREEL Overview: Offline and Online Evaluation of Stream-based News Recommender Systems. In: Working Notes of CLEF 2017: Conference and Labs of the Evaluation Forum, Dublin, Ireland, 11-14 Sept 2017, (Accepted for Publication)

[img] Text
143586.pdf - Accepted Version
Restricted to Repository staff only

790kB

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 explained.

Item Type:Conference Proceedings
Status:Accepted for Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Hopfgartner, Dr Frank
Authors: Kille, B., Lommatzsch, A., Hopfgartner, F., Larson, M., and Brodt, T.
College/School:College of Arts > School of Humanities > Humanities Advanced Technology and Information Institute (HATII)

University Staff: Request a correction | Enlighten Editors: Update this record