Hybrid Recommender System via Personalized Users’ Context

Nosshi, Anthony; Asem, Aziza; Senousy, Mohamed Badr

doi:10.2478/cait-2019-0006

Abstract

In movie domain, finding the appropriate movie to watch is a challenging task. This paper proposes a recommender system that suggests movies in cinema that fit the user’s available time, location, mood and emotions. Conducted experiments for evaluation showed that the proposed method outperforms the other baselines.

References

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Hybrid Recommender System via Personalized Users’ Context

Abstract

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