Workshop on reproducibility and replication in recommender systems evaluation - RepSys
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
ACMDate
2013Citation
10.1145/2507157.2508006
RecSys '13: Proceedings of the 7th ACM conference on Recommender systems, ACM, 2013. 485-486
ISBN
978-1-4503-2409-0DOI
10.1145/2507157.2508006Funded by
This workshop was carried out during the tenure of an ERCIM “Alain Bensoussan” Fellowship Programme, funded by European Comission FP7 grant agreement no.246016.Project
info:eu-repo/grantAgreement/EC/FP7/246016Editor's Version
http://dx.doi.org/10.1145/2507157.2508006Subjects
Evaluation; Experimental design; Experimental methodology; Replicability; Reproducibility; InformáticaNote
This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in RecSys '13 Proceedings of the 7th ACM conference on Recommender systems, http://dx.doi.org/10.1145/2507157.2508006.Rights
© 2013 the owner/author(s)Abstract
Experiment replication and reproduction are key requirements for empirical research methodology, and an important open issue in the field of Recommender Systems. When an experiment is repeated by a different researcher and exactly the same result is obtained, we can say the experiment has been replicated. When the results are not exactly the same but the conclusions are compatible with the prior ones, we have a reproduction of the experiment. Reproducibility and replication involve recommendation algorithm implementations, experimental protocols, and evaluation metrics. While the problem of reproducibility and replication has been recognized in the Recommender Systems community, the need for a clear solution remains largely unmet, which motivates the present workshop.
Files in this item
Google Scholar:Bellogin Kouki, Alejandro
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Castells Azpilicueta, Pablo
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Said, Alan
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Tikk, Domonkos
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