Group Inspired Single-User Collaborative Filtering
نویسنده
چکیده
Personalized recommendation is well researched area, but the group recommendation still needs to be explored. In this paper we propose an idea of approach for the single user recommendation based on the principles of the group recommendation. We explore several setting of such an approach in order to the group size or the number of similar users used for the recommendation. Experiments are performed over the standard MovieLens dataset and proposed approach is compared to the standard collaborative recommender. Obtained results support hypothesis that proposed approach brings statistically significant improvement and thus can be used for the standard recommendation.
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