移动环境下基于情境感知的个性化影视推荐算法研究

iming at the problem of low accuracy in the use of traditional recommendation algorithm in mobile environment, a matrix factorization algorithm based on context-aware was proposed. Based on the basic matrix factorization algorithm, the algorithm performed unknown score prediction by incorporating global bias and context bias. The advantage of this algorithm is that, on the one hand, the matrix factorization was used to make the scale of the matrix much smaller than the original scoring matrix; on the other hand, the algorithm fully integrated the influence of the situational elements on the score, making the prediction score more accurate. Experiments on the LDOS-CoMoDa dataset show that the proposed algorithm outperforms the user-based collaborative filtering algorithm, the basic matrix factorization algorithm and Baseline prediction algorithm.