Kille, B., Lommatzsch, A., Gebremeskel, G.G. et al. (7 more authors) (2016) Overview of NewsREEL’16: Multi-dimensional evaluation of real-time stream-recommendation algorithms. In: Experimental IR Meets Multilinguality, Multimodality, and Interaction. International Conference of the Cross-Language Evaluation Forum for European Languages, 05-08 Sep 2016, Évora, Portugal. Lecture Notes in Computer Science, 9822 . Springer , pp. 311-331. ISBN 978-3-319-44563-2
Abstract
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news recommendation and to optimize and evaluate their recommender algorithms both online and offline. In this paper, we summarize the objectives and challenges of NewsREEL 2016. We cover two contrasting perspectives on the challenge: that of the operator (the business providing recommendations) and that of the challenge participant (the researchers developing recommender algorithms). In the intersection of these perspectives, new insights can be gained on how to effectively evaluate real-time stream recommendation algorithms.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer International Publishing Switzerland 2016. This is an author-produced version of a paper subsequently published in Fuhr N. et al. (eds) Experimental IR Meets Multilinguality, Multimodality, and Interaction. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Recommender Systems; News; Multi-dimensional Evaluation; Living Lab; Stream-based Recommender |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 Jun 2019 10:24 |
Last Modified: | 20 Jun 2019 10:31 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-319-44564-9_27 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:147611 |