Abstract
Currently, most of the recommendation systems use user’s feedbacks to suggest an item for the user. However, the current recommendation system used only explicit rating information, which not fully evaluating the factors that directly affect the feeling of users in rating. To achieve more accurate results, this paper proposes a solution to add the implicit effect of items rating to the recommendation system based on the TrustSVD model and matrix factorization (MF) techniques. The experimental results showed our proposed solution achieve better than 18% the matrix factorization method and 15% the Multi-Relational Matrix Factorization method.
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Nguyen, T.D.A., Vu, T.N., Le, T.D. (2019). The Implicit Effect of Items Rating on Recommendation System. In: Dang, T., Küng, J., Takizawa, M., Bui, S. (eds) Future Data and Security Engineering. FDSE 2019. Lecture Notes in Computer Science(), vol 11814. Springer, Cham. https://doi.org/10.1007/978-3-030-35653-8_47
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DOI: https://doi.org/10.1007/978-3-030-35653-8_47
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