ONLINE EVALUATION OF RECOMMENDER SYSTEM WITH MOVIELENS DATASET
Journal Title: Journal of Information Technology and Application (JITA) - Year 2016, Vol 6, Issue 1
Abstract
The purpose of this paper is to explore the advantages of recommender systems based on the matrix factorization in respect to classical first neighbor recommender systems to real users through A/B test, as these studies are more signifi cant. The results presented in this paper confi rms the hypothesis that the recommender systems based on the models of matrix factorization are superior in relation to classical nearest-neighbor recommender systems.
Authors and Affiliations
Asmir Handžić
Keywords
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- EP ID EP226488
- DOI 10.7251/JIT16020H
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