Research on Personalized Adaptive Resource Recommendation Algorithm Based on Learning Style
Personalized adaptive resource recommendation is a learner-centered process,which is based on artificial intelli-gence and big data technology,simulated human thinking to carry out learning resource recommendation.In this paper,the learner model and resource model are constructed separately on the basis of analyzing the learning styles of learners and resources,the re-search of recommendation algorithms on personalized and adaptive resource recommendation based on learning style filtering,col-laborative filtering and association rules,which used to carry out.Results show that hybrid adaptive recommendation based on learn-ing style are more in line with the personalized learning needs of learners.
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