Workshop on reproducibility and replication in recommender systems evaluation - RepSys
Entidad
UAM. Departamento de Ingeniería InformáticaEditor
ACMFecha de edición
2013Cita
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
10.1145/2507157.2508006Financiado por
This workshop was carried out during the tenure of an ERCIM “Alain Bensoussan” Fellowship Programme, funded by European Comission FP7 grant agreement no.246016.Proyecto
info:eu-repo/grantAgreement/EC/FP7/246016Versión del editor
http://dx.doi.org/10.1145/2507157.2508006Materias
Evaluation; Experimental design; Experimental methodology; Replicability; Reproducibility; InformáticaNota
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.Derechos
© 2013 the owner/author(s)Resumen
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.
Lista de ficheros
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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