Random Performance Differences Between Online Recommender System Algorithms
In the evaluation of recommender systems, the quality of recommendations made by a newly proposed algorithm is compared to the state-of-the-art, using a given quality measure and dataset. Validity of the evaluation depends on the assumption that the evaluation does not exhibit artefacts resulting from the process of collecting the dataset. The main difference between online and offline evaluation is that in the online setting, the user’s response to a recommendation is only observed once. We used the NewsREEL challenge to gain a deeper understanding of the implications of this difference for making comparisons between different recommender systems. The experiments aim to quantify the expected degree of variation in performance that cannot be attributed to differences between systems. We classify and discuss the non-algorithmic causes of performance differences observed.
This research was partially supported by COMMIT project Infiniti.
- 1.Beel, J., Genzmehr, M., Langer, S., Nürnberger, A., Gipp, B.: A comparative analysis of offline and online evaluations and discussion of research paper recommender system evaluation. In: Proceedings of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation, pp. 7–14. ACM (2013)Google Scholar
- 2.Brodt, T., Hopfgartner, F.: Shedding light on a living lab: the clef newsreel open recommendation platform. In: Proceedings of the 5th Information Interaction in Context Symposium, pp. 223–226. ACM (2014)Google Scholar
- 3.Garcin, F., Faltings, B., Donatsch, O., Alazzawi, A., Bruttin, C., Huber, A.: Offline and online evaluation of news recommender systems at swissinfo. In: Proceedings of the 8th ACM Conference on Recommender Systems, pp. 169–176. ACM (2014)Google Scholar
- 4.Hopfgartner, F., Kille, B., Lommatzsch, A., Plumbaum, T., Brodt, T., Heintz, T.: Benchmarking news recommendations in a living lab. In: Kanoulas, E., Lupu, M., Clough, P., Sanderson, M., Hall, M., Hanbury, A., Toms, E. (eds.) CLEF 2014. LNCS, vol. 8685, pp. 250–267. Springer, Heidelberg (2014)Google Scholar
- 5.Howard, S.: Abba: Frequently asked questions. https://www.thumbtack.com/labs/abba/. Accessed 18 July 2016
- 7.McNee, S.M., Kapoor, N., Konstan, J.A.: Don’t look stupid: avoiding pitfalls when recommending research papers. In: Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work, pp. 171–180. ACM (2006)Google Scholar