Personalised push of ideological and political network teaching resources based on user characteristics

To address the problems of low accuracy and AUC value in traditional personalised push methods for ideological and political network teaching resources, a personalised push method of ideological and political network teaching resources based on user characteristics is proposed. By leveraging a knowledge graph to analyse user preference data, in order to extract user preference features. Using the extracted preference features and combined with the information of ideological and political teaching resources, a model for pushing ideological and political network teaching resources is constructed, which includes four modules: resource encoding layer, candidate perception layer, multi interest extraction layer, and click prediction layer, to achieve the function of resource pushing. The experimental results show that the push accuracy of the proposed method is higher than 94.9%, and the AUC value is of 0.894, indicating strong practical applicability.