Abstract
Recommendation is a very important part of our digital lives. Without recommendation one can get lost in web of data. Movies are also very important form of entertainment. We watch most movies that are recommended by someone or others. Each person likes specific type of movies. So movie recommendation system can increase sales of a movie rent/sales shop. Websites like Netflix are using it. But there is one problem that can cause recommendation system to fail. This problem is sparsity problem. In this paper, we have used a new approach that can solve sparsity problem to a great extent.
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Mishra, N., Chaturvedi, S., Mishra, V., Srivastava, R., Bargah, P. (2017). Solving Sparsity Problem in Rating-Based Movie Recommendation System. In: Behera, H., Mohapatra, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 556. Springer, Singapore. https://doi.org/10.1007/978-981-10-3874-7_11
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DOI: https://doi.org/10.1007/978-981-10-3874-7_11
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