Open Access

Hybrid Recommender System via Personalized Users’ Context

,  and   
Mar 29, 2019

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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.

Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Information Technology