Abstract
Recommender systems are a representation of user choices for the purpose of suggesting items to view or purchase. The Intelligent movie recommender system that is proposed combines the concept of Human-Computer Interaction and Machine Learning. The proposed system is a subclass of information filtering system that captures facial feature points as well as emotions of a viewer and suggests them movies accordingly. It recommends movies best suited for users as per their age and gender and also as per the genres they prefer to watch. The recommended movie list is created by the cumulative effect of ratings and reviews given by previous users. A neural network is trained to detect genres of movies like horror, comedy based on the emotions of the user watching the trailer. Thus, proposed system is intelligent as well as secure as a user is verified by comparing his face at the time of login with one stored at the time of registration. The system is implemented by a fully dynamic interface i.e. a website that recommends movies to the user [22].
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Mahata, A., Saini, N., Saharawat, S., Tiwari, R. (2017). Intelligent Movie Recommender System Using Machine Learning. In: Basu, A., Das, S., Horain, P., Bhattacharya, S. (eds) Intelligent Human Computer Interaction. IHCI 2016. Lecture Notes in Computer Science(), vol 10127. Springer, Cham. https://doi.org/10.1007/978-3-319-52503-7_8
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