Abstract
Recommender systems have been explored with different research techniques including content-based filtering and collaborative filtering. The main issue is with the cold start problem of how recommendations have to be suggested to a new user in the platform. There is a need for a system which has the ability to recommend items similar to the user’s demographic category by considering the collaborative interactions of similar categories of users. The proposed hybrid model solves the cold start problem using collaborative, demography, and content-based approaches. The base algorithm for the hybrid model SVDpp produced a root mean squared error (RMSE) of 0.92 on the test data.
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Raju, B.K., Ummesalma, M. (2022). Demography-Based Hybrid Recommender System for Movie Recommendations. In: Aurelia, S., Hiremath, S.S., Subramanian, K., Biswas, S.K. (eds) Sustainable Advanced Computing. Lecture Notes in Electrical Engineering, vol 840. Springer, Singapore. https://doi.org/10.1007/978-981-16-9012-9_5
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DOI: https://doi.org/10.1007/978-981-16-9012-9_5
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