一种用户偏好的美学图像推荐方法 postprint

Abstract: With the rapid development and popularization of the Internet and multimedia camera technology, the number of various image resources has expanded dramatically. How to quickly and effectively find the user's favorite image in many image information resources has become an important issue that needs to be solved in the field of image recommendation. Aiming at this problem, this paper proposed a user-appreciated aesthetic image recommendation method, which used the deep convolutional neural network to extract the deep features of the image, and obtained an image sorting score after SVMRank, while using hand-marked image aesthetic factors (such as : hue method, image combination rule, definition and simplicity) Calculate and obtain the aesthetic characteristics of the image, get an aesthetic score, and finally perform weighted cross-validation to obtain a recommendation result that is satisfactory to the user. Experiments show that the algorithm is an effective recommendation method for aesthetic preferences.