Stream-Based Recommendations: Online and Offline Evaluation as a Service

@inproceedings{Kille2015StreamBasedRO,
  title={Stream-Based Recommendations: Online and Offline Evaluation as a Service},
  author={Benjamin Kille and A. Lommatzsch and R. Turrin and Andr{\'a}s Ser{\'e}ny and M. Larson and Torben Brodt and J. Seiler and F. Hopfgartner},
  booktitle={CLEF},
  year={2015}
}
Providing high-quality news recommendations is a challenging task because the set of potentially relevant news items changes continuously, the relevance of news highly depends on the context, and there are tight time constraints for computing recommendations. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to evaluate and optimize news recommender algorithms online and offline. In this paper, we discuss the objectives and challenges of the NewsREEL lab. We… Expand
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References

SHOWING 1-10 OF 27 REFERENCES
Offline and online evaluation of news recommender systems at swissinfo.ch
  • 110
  • PDF
Real-time recommendations for user-item streams
  • 30
Workshop and challenge on news recommender systems
  • 17
  • PDF
Recommender Systems Evaluation: A 3D Benchmark
  • 37
  • PDF
InBeat: Recommender System as a Service
  • 5
  • PDF
Overview of CLEF NewsREEL 2015: News Recommendation Evaluation Lab
  • 26
  • PDF
Shedding light on a living lab: the CLEF NEWSREEL open recommendation platform
  • 36
  • PDF
Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols
  • 307
  • PDF
...
1
2
3
...