Personalized Recommendation Method for the Video Teaching Resources of Folk Sports Shehuo Based on Mobile Learning

Xunxian Shehuo is a kind of sports project which gathers many kinds of folk customs, and it is the key to develop the national fitness strategy. Folk sports social fire video teaching resources are so large that it is difficult for learners to find the content they are interested in from a lot of information. Based on mobile learning theory, this paper constructs a learner model by analyzing learner characteristics, collecting learner data and representing learner characteristics. Weighted the learner behavior, obtained the characteristics of learner interest preferences, and calculated the similarity between learner interest preferences and teaching resources. Through collaborative filtering recommendation algorithm to obtain the best teaching resources personalized recommendation results. The experimental results show that the maximum recall rate and the maximum accuracy rate are 96% and 98%, which fully proves the effectiveness of the proposed method.