Accurate Recommendation Algorithm of Digital Resources in Ideological And Political Mobile Teaching Based on Collaborative Filtering

At present, the recommendation of teaching resources only depends on the score of resource acquisition, which leads to low accuracy of recommended resources and low efficiency of recommendation algorithm. In order to improve the above defects, this paper will study the accurate recommendation algorithm of digital resources of ideological and political mobile teaching based on collaborative filtering. Through implicit and explicit mining of teaching resource data, the user's preference is calculated, and the resource recommendation data related to similar users is obtained. SCROM(Sharable Content Object Reference Model) is used to manage the digital resources of ideological and political education, and the calling process of resource content is simple. After the collaborative filtering algorithm is improved, the resources are accurately recommended according to the comprehensive score. In the test of the algorithm, the accuracy rate of resource recommendation by using the improved collaborative filtering algorithm is maintained above 75%, and the recommendation efficiency is greatly improved, with good recommendation effect.