Abstract
Movie Recommendations Systems are a common practice by most of the online stores today. The web based movie recommendation systems makes predictions about the responses of the users based on their search history or known preferences. Recommendation of items is usually done based on the properties or content of the item or collaboration of the user’s ratings, and by using intelligent algorithms that include classification or clustering techniques. Accurate prediction of what the customer may likely to busy or the user my visit is of utmost important, as it benefits both the service providers and customers. This chapter provides the evolution, fundamental concepts, classification, traditional and novel models, requirements, similarity measures, evaluation approaches, issues, challenges, impacts due to social networking, and future of movie recommendation systems.
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Das, N., Borra, S., Dey, N., Borah, S. (2018). Social Networking in Web Based Movie Recommendation System. In: Dey, N., Babo, R., Ashour, A., Bhatnagar, V., Bouhlel, M. (eds) Social Networks Science: Design, Implementation, Security, and Challenges . Springer, Cham. https://doi.org/10.1007/978-3-319-90059-9_2
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DOI: https://doi.org/10.1007/978-3-319-90059-9_2
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