A Recommendation Algorithm for Online English Reading Courses in Higher Vocational Colleges Based on Differential Privacy

The current logic of recommending online reading courses for vocational college English is generally one-way hierarchy, with limited recommended scope. Moreover, the large number of online reading courses leads to a decrease in the precision of recommending suitable courses for each learner. In order to address this issue, a design and analysis of a differential privacy-based algorithm for recommending online reading courses for vocational college English is proposed. According to the actual recommendation needs and standards, we first collect the characteristics of English reading course recommendations, break the limits of the recommendation range, establish multi-level recommendation calculation logic, and use in-depth differential recommendation reconstruction to achieve recommendation calculation processing. The final test results show that for the four groups, the recommended accuracy ratio can all reach above 5, and the course recommendation coverage and accuracy are above 80%. This indicates that the English reading course recommendation algorithm has high measurement efficiency, strong pertinence, better recommendation effect, and practical application value.