Fig 1.
The extraction of relationship feature information of “User-Movie”.
Fig 2.
Regression model based on SVM classification for personalized recommendation.
Table 1.
Summary of the MovieLens 1M data set.
Fig 3.
Accuracy of recommended models based on four methods.
Table 2.
The average classification accuracy (%) of four algorithms.
Fig 4.
The parameters optimization curve corresponds to IPSO algorithm.
Fig 5.
The parameters optimization curve corresponds to GA.
Fig 6.
The parameters optimization curve corresponds to GS algorithm.
Fig 7.
The MAE of ratings based on six methods.
It shows the comparison results of the regression based on classification, SVM direct regression, User-based collaborative filtering, Item-based collaborative filtering, BP neural network, and Multiple linear regression.