Research on personalized resource recommendation algorithm for parent education

Because of the single teaching mode, the extreme imbalance of educational resources and the low efficiency of education, the traditional parent education can no longer meet the requirements of educational informationization. Therefore, in order to improve the learning efficiency of learners, the research introduces collaborative filtering algorithm based on the construction of personalized recommendation model, and verifies its effectiveness while improving it. The experimental results show that, compared with Random algorithm, the accuracy of User based Collaborative Filtering (UBCF) algorithm is 65.53%, which is much better than Random algorithm; Among the three different methods, the accuracy of collaborative filtering algorithm is the highest, reaching 67.92%, and the performance of this method is the best under the same data. In a word, in parent education, collaborative filtering algorithm can effectively improve the accuracy of recommendation results and help parents find deficiencies in the teaching process.