Research on English Learning Resource Query System Based on Collaborative Filtering Recommendation Algorithm

Abstract

The collaborative filtering algorithm can comprehensively consider the historical evaluation information of the users in the system, calculating the corresponding users, and then finding the resources that the users may be interested in through the evaluation of teaching resources by similar users. Compared with the content-based recommendation algorithm, the collaborative filtering algorithm can find the new interests of users, which can achieve leaping recommendations. This article focuses on the present setting of modern English education and the particular application strategies of applying the latest techniques to improve English learning resource query, reviewing the existing strategies for the improvement of the reliability and validity of language study for online English learning, and looking forward to the direction of follow-up research and practice of online resource query system for virtual language study in the era of big data, which has a certain practical reference meaning for the improvement of English teaching theory under the context of the continuous maturity in the area of AI.