Design of English Autonomous Learning System Based on Collaborative Recommendation Algorithm

Authors

  • Zhan Wang, Xueqing Yue*

Abstract

This paper first analyzes the common problems of traditional collaborative filtering technology in English autonomous learning system, and then proposes an improved collaborative filtering algorithm. This algorithm introduces the concept of user behavior weight value to alleviate the common cold start problem of collaborative filtering algorithm. Secondly, the collaborative filtering technology is combined with online English autonomous learning resources, and the personalized recommendation system of online English autonomous learning resources is designed. The system realizes the functions of learner's self-learning, self-evaluation and resource sharing, and improves the learning effect of learners. Although the content of online English autonomous learning resources will not change, but with the deepening of user learning, learning interest and direction may change. How to make real-time recommendation according to the change of user interest needs to be studied deeply. The experimental data show that the system can improve the efficiency of English autonomous learning and achieve accurate user interest matching.

Published

2020-12-31

Issue

Section

Articles