The Impact of a Popularity Punishing Hyperparameter on ItemKNN Recommendation Performance-Reference-Cited by-同舟云学术

The Impact of a Popularity Punishing Hyperparameter on ItemKNN Recommendation Performance

Published:2023 Issue: Volume: Page:646-654
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Verachtert Robin^ORCID,Craps Jeroen^ORCID,Michiels Lien^ORCID,Goethals Bart^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-28238-6_56

Reference24 articles.

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2. Abdollahpouri, H., Mansoury, M., Burke, R., Mobasher, B.: The unfairness of popularity bias in recommendation. In: CEUR Workshop Proceedings, vol. 2440 (2019). https://ceur-ws.org/Vol-2440/paper4.pdf

3. Bambini, R., Cremonesi, P., Turrin, R.: A recommender system for an IPTV service provider: a real large-scale production environment. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 299–331. Springer, Boston (2011). https://doi.org/10.1007/978-0-387-85820-3_9

4. 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, RepSys 2013, pp. 7–14. Association for Computing Machinery, New York (2013). https://doi.org/10.1145/2532508.2532511. ISBN 9781450324656

5. Beel, J., Langer, S.: A comparison of offline evaluations, online evaluations and user studies in the context of research-paper recommender systems. In: Kapidakis, S., Mazurek, C., Werla, M. (eds.) Research and Advanced Technology for Digital Libraries, pp. 153–168. Springer Cham (2015). https://doi.org/10.1007/978-3-319-24592-8_12. ISBN 978-3-319-24592-8

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