Retrieval and Recommendation of English Learning Resources Based on Knowledge Correlation

Abstract

The design of retrieval and recommendation method of personalized learning resources based on students’ cognition level of professional knowledge and the correlation degree of the knowledge is of certain practical significance. In reality, students’ learning preferences and needs will change with the passing of time and the upgrading of learning stages, so giving learning resource recommendations without considering the time series features of students’ needs for learning resources cannot guarantee students' learning efficiency or the effect of personal knowledge system perfection. To solve this problem, this paper took online English learning as an example to study the retrieval and recommendation of English learning resources based on knowledge correlation. At first, the paper gave the relationship between the knowledge points of English learning resources, and gave judgements on students’ mastery degree of knowledge points. Then, the influence of the semantics and relationships of knowledge points involved in English learning was fully considered, and the closeness degree of the correlation of learning resources was calculated. At last, this paper introduced a hybrid attention mechanism into the learning resource recommendation model, and gave the process for calculating the weight of hybrid attention. The effectiveness of the constructed model was verified by the experimental results.