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
overview over the implemented approaches and discusses the evaluation results. In addition, the main results of Living Lab and the Replay task are explaine
Original language | English |
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Title of host publication | CLEF 2017 Working Notes |
Subtitle of host publication | Conference and Labs of the Evaluation Forum |
Editors | Linda Cappellato, Nicola Ferro, Lorraine Goeuriot, Thomas Mandl |
Publisher | CEUR-WS |
Pages | 1-13 |
Number of pages | 13 |
Publication status | Published - 2017 |
Event | CLEF 2017 - Conference and Labs of the Evaluation Forum: Information Access Evaluation meets Multilinguality, Multimodality, amd Visualization - Dublin, Ireland Duration: 11 Sept 2017 → 14 Sept 2017 Conference number: 8 http://clef2017.clef-initiative.eu/ |
Publication series
Name | CEUR Workshop Proceedings |
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Publisher | CEUR |
Volume | 1866 |
ISSN (Electronic) | 1613-0073 |
Conference
Conference | CLEF 2017 - Conference and Labs of the Evaluation Forum |
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Country/Territory | Ireland |
City | Dublin |
Period | 11/09/17 → 14/09/17 |
Internet address |
Keywords
- recommender systems
- news
- multi-dimensional evaluation
- living lab
- stream-based recommender