An asymmetric graph recommendation algorithm based on user scores and interests
Yiwen Zhang, Ran Wang, Tingwei Wang, Guang-Da He, Jun Hu · IOP Conference Series Materials Science and Engineering · 2017
The proposed algorithm uses the symmetry similarity calculation method based on the common project, which can not reflect the user's interest very well and the recommendation accuracy is low. In order to improve the accuracy of recommendation, this paper proposes a graph recommendation algorithm which integrates user rating and interest. In order to reflect the interests of users, using the principle of diffusion of the substance user rating information asymmetry; Experiments show that the proposed algorithm for user rating and interest fusion improves the prediction accuracy.