Adaptive Recommendation Algorithm of English Reading Learning Resources Based on Collaborative Filtering

The rapid development of the Internet has promoted the emergence of a large number of English learning resources and online education platforms. However, the massive resources and learning methods have also led to the emergence of the dilemma of information overload, and it has become quite difficult for users to quickly obtain the information they are interested in. Therefore, it is one of the current research hotspots in the field of education to study a highly automated personalized learning adaptive recommendation model to recommend a learning plan suitable for the learner's own learning situation for a specific course or field. Based on the collaborative filtering algorithm model, this paper integrates the depth of user English learning, the collaborative topic regression model based on social regularization and the collaborative deep learning model based on social regularization, and finally generates a personalized English reading learning plan.