Based on the understanding and comparison of various main recommendation algorithms, this paper focuses on the collaborative filtering algorithm and proposes a collaborative filtering recommendation algorithm with improved user model. Firstly, the algorithm considers the score difference caused by different user scoring habits when expressing preferences and adopts the decoupling normalization method to normalize the user scoring data; secondly, considering the forgetting shift of user interest with time, the forgetting function is used to simulate the forgetting law of score, and the weight of time forgetting is introduced into user score to improve the accuracy of recommendation; finally, the similarity calculation is improved when calculating the nearest neighbor set. Based on the Pearson similarity calculation, the effective weight factor is introduced to obtain a more accurate and reliable nearest neighbor set. The algorithm establishes an offline user model, which makes the algorithm have better recommendation efficiency. Two groups of experiments were designed based on the mean absolute error (MAE). One group of experiments tested the parameters in the algorithm, and the other group of experiments compared the proposed algorithm with other algorithms. The experimental results show that the proposed method has better performance in recommendation accuracy and recommendation efficiency.

Aiming at the different levels of college English education, and finding problems and countermeasures in time, this paper puts forward a research on college English education reform under the cultural differences between China and foreign countries. Exploring the cultural background behind the learning of English knowledge, China and foreign countries have formed two completely different cultural forms, resulting in differences in language communication, behavioral expression, way of thinking, and living habits between China and foreign countries. Advocate and motivate students to learn Chinese and Western cultures, cultivate students’ cross-cultural awareness, actively explore English language and culture, and apply modern teaching methods to college English teaching. Mining high-quality parameters to quickly obtain target data, set reasonable control factors, and calculate the information gain of data attributes. Using differentiated information reorganization, a distributed recursive statistical analysis model of students’ English grades was established, the characteristic parameters of grade differences were analyzed, the optimal lag order was selected for the prediction error index, and the co-integration relationship of test variables of students’ grade differences was realized. The results of the study show that the classes that have undergone reformed education combined with Chinese and foreign countries have significantly improved their college English, with an average score of over 89.