Firstly, this paper proposes a hybrid nearest neighbor collaborative filtering algorithm based on user rating ,we talk about several existing collaborative filtering algorithms and the existing problems of the current algorithm, and compares it (not accurate) with the classical algorithm: itembased collaborative filtering algorithm, and compares it with several popular recommendation algorithms. The nearest neighbor idea is used to solve the problem of degraded accuracy caused by sparse data. User rating attributes are used to conclude recommendation with better accuracy and improved quality .In this paper ,we use MoiveLens data set, sorting algorithm in machine learning ，and analyze the advantages and disadvantages of different algorithms through vertical and horizontal comparison. Intelligent recommendation is realized by machine learning, intelligent information processing and intelligent control decisionmaking can help us to derive better recommendations, and good results are achieved in intelligent control.