Personalized recommendation system of blended English teaching resources based on deep learning

In order to improve the quality of blended English teaching, a personalized recommendation system of blended English teaching resources based on deep learning is proposed. Analyze the functional architecture of the system, and design user registration module, crawler module and personalized recommendation module of teaching resources. It is used for user registration, crawling of blended English teaching resources and personalized recommendation of teaching resources. The system software part calculates the user interest similarity, and uses the neural network in deep learning to calculate the interest preference data, so as to obtain the recommendation results of teaching resources. The experimental results show that compared with the traditional teaching resource recommendation system, this system can accurately calculate the user interest similarity, so as to improve the recommendation accuracy, so it obtains higher user satisfaction.