关键词: 时间偏差, 因子分解, 推荐精度, 梯度下降

Abstract: In view of the problem of low accuracy in the traditional recommendation algorithm. The neighborhood factor decomposition recommendation algorithm based on time deviation information（NFDRA） is presented. The main part of it is factorization algorithm, stochastic gradient descent optimization is complementary, and the integration of user ratings neighborhood information and time deviation. The experiments show, the neighborhood factor decomposition recommendation algorithm based on time deviation information, can get more accurate results and have significant difference.

Key words: time deviation, factorization, accuracy of recommendation, gradient descent